https://simplecast.com AI Loves Data Podcast The official podcast of Data Science Salon which is now AI Loves Data. We interview top and rising luminaries in data science, machine learning, and AI on the trends and business use cases that are propelling the field forward. The AI Loves Data series is a unique vertical focused conference which brings together specialists face-to-face to educate each other, illuminate best practices, and innovate new solutions in a casual atmosphere with food, great coffee, and entertainment. 2026 AI Loves Data en Tue, 24 Mar 2026 05:00:00 +0000 Tue, 24 Mar 2026 05:00:14 +0000 https://data-science-salon-podcast.simplecast.com AI Loves Data Podcast https://image.simplecastcdn.com/images/61151926-39da-4992-ab93-795418d2be18/9101ff7a-847c-4c25-8caa-e28b82e3eb21/3000x3000/aldpodcastlogo.jpg?aid=rss_feed https://data-science-salon-podcast.simplecast.com episodic The official podcast of Data Science Salon which is now AI Loves Data. We interview top and rising luminaries in data science, machine learning, and AI on the trends and business use cases that are propelling the field forward. The AI Loves Data series is a unique vertical focused conference which brings together specialists face-to-face to educate each other, illuminate best practices, and innovate new solutions in a casual atmosphere with food, great coffee, and entertainment. Data Science Salon false https://feeds.simplecast.com/AIdDG__5 data science, ml, ai, artificial intelligence, big data, data, data scientist, machine learning Data Science Salon now AI Loves Data anna@formulatedby.com edc7ff13-0713-4323-b722-1b284f492832 Scaling LLM-Powered Recommender Systems and AI Infrastructure Key Highlights:

  • Production-Scale LLMs: Deploying and scaling recommender systems powered by large language models.
  • AI Infrastructure Challenges: Building reliable, high-performance search and ML platforms at global scale.
  • MLOps & Model Optimization: Lessons learned from optimizing and monitoring complex AI pipelines.
  • Future of AI at Scale: Trends in GenAI, multimodal AI, and recommender systems that will shape the industry.

🎧 Tune in to Episode 63 to hear Rahul Raja’s insights on creating scalable, reliable, and cutting-edge AI infrastructure for production-grade systems.

Be sure to mark your calendars for the annual ALD NYC on May 13, where we will focus on THE FUTURE OF APPLIED AI IN Finance and Banking. Join us to hear from experts on how AI is shaping the future of finance, banking and insurance: https://ailovesdata.com/newyork/ 

]]> Tue, 24 Mar 2026 05:00:00 +0000 anna@formulatedby.com (Anna Anisin) https://data-science-salon-podcast.simplecast.com/episodes/scaling-llm-powered-recommender-systems-and-ai-infrastructure-2otxo7kb Key Highlights:

  • Production-Scale LLMs: Deploying and scaling recommender systems powered by large language models.
  • AI Infrastructure Challenges: Building reliable, high-performance search and ML platforms at global scale.
  • MLOps & Model Optimization: Lessons learned from optimizing and monitoring complex AI pipelines.
  • Future of AI at Scale: Trends in GenAI, multimodal AI, and recommender systems that will shape the industry.

🎧 Tune in to Episode 63 to hear Rahul Raja’s insights on creating scalable, reliable, and cutting-edge AI infrastructure for production-grade systems.

Be sure to mark your calendars for the annual ALD NYC on May 13, where we will focus on THE FUTURE OF APPLIED AI IN Finance and Banking. Join us to hear from experts on how AI is shaping the future of finance, banking and insurance: https://ailovesdata.com/newyork/ 

]]> Scaling LLM-Powered Recommender Systems and AI Infrastructure Anna Anisin 00:23:29 In this episode of the AI Loves Data Podcast, we sit down with Rahul Raja, Staff Engineer at LinkedIn, who leads large-scale AI and search infrastructure projects. Rahul shares his experience deploying LLM-powered recommender systems and building production-scale AI/ML infrastructure that supports millions of users. Have questions or comments, let us know: info@formulatedby.com In this episode of the AI Loves Data Podcast, we sit down with Rahul Raja, Staff Engineer at LinkedIn, who leads large-scale AI and search infrastructure projects. Rahul shares his experience deploying LLM-powered recommender systems and building production-scale AI/ML infrastructure that supports millions of users. Have questions or comments, let us know: info@formulatedby.com data scientists, mlops, data science, llms, artificial intelligence, ai, machine learning false full 63 bdeca6b0-5b93-49bc-98a4-43b24bd4f57c Bridging Technology and Business: Operationalizing AI Vaishali shares her experience leading global data teams, partnering with executive leadership, and building strategies that connect cutting-edge technology to real business value. We explore her insights on operationalizing AI, scaling analytics across enterprises, and overcoming challenges in data governance, stakeholder alignment, and innovation adoption.

Key Highlights:

  • Bridging Tech and Business: How Vaishali connects AI and analytics innovations to organizational strategy and measurable outcomes.
  • Global Team Leadership: Lessons from managing cross-functional, geographically distributed teams and driving collaboration.
  • Operational Optimization: Examples of initiatives that reduced operational complexity while improving efficiency.
  • Scaling Analytics and AI: Best practices for governance, workflow, and embedding AI into enterprise decision-making.
  • Emerging Trends: Vaishali’s perspective on the next wave of AI, analytics, and enterprise data strategies.

Tune in to Episode 61 to learn how Vaishali Lambe drives data-driven transformation, operational excellence, and AI innovation across global enterprises.

Be sure to mark your calendars for the 10th annual ALD NYC on May 13, where we will focus on GENAI AND INTELLIGENT AGENTS IN THE FINANCE AND BANKING. Join us to hear from experts on how AI is shaping the future of the enterprise. https://www.datascience.salon/new-york/

]]> Tue, 17 Feb 2026 06:00:00 +0000 anna@formulatedby.com (Vaishali Lambe, Anna Anisin) https://data-science-salon-podcast.simplecast.com/episodes/bridging-technology-and-business-operationalizing-ai-_jAOkc7d Vaishali shares her experience leading global data teams, partnering with executive leadership, and building strategies that connect cutting-edge technology to real business value. We explore her insights on operationalizing AI, scaling analytics across enterprises, and overcoming challenges in data governance, stakeholder alignment, and innovation adoption.

Key Highlights:

  • Bridging Tech and Business: How Vaishali connects AI and analytics innovations to organizational strategy and measurable outcomes.
  • Global Team Leadership: Lessons from managing cross-functional, geographically distributed teams and driving collaboration.
  • Operational Optimization: Examples of initiatives that reduced operational complexity while improving efficiency.
  • Scaling Analytics and AI: Best practices for governance, workflow, and embedding AI into enterprise decision-making.
  • Emerging Trends: Vaishali’s perspective on the next wave of AI, analytics, and enterprise data strategies.

Tune in to Episode 61 to learn how Vaishali Lambe drives data-driven transformation, operational excellence, and AI innovation across global enterprises.

Be sure to mark your calendars for the 10th annual ALD NYC on May 13, where we will focus on GENAI AND INTELLIGENT AGENTS IN THE FINANCE AND BANKING. Join us to hear from experts on how AI is shaping the future of the enterprise. https://www.datascience.salon/new-york/

]]> Bridging Technology and Business: Operationalizing AI Vaishali Lambe, Anna Anisin 00:38:26 In this episode of the AI Loves Data Podcast, host, Anna Anisin sits down with Vaishali Lambe, an accomplished Data & AI Executive recognized globally for driving operational optimization, strategic growth, and impactful AI initiatives. In this episode of the AI Loves Data Podcast, host, Anna Anisin sits down with Vaishali Lambe, an accomplished Data & AI Executive recognized globally for driving operational optimization, strategic growth, and impactful AI initiatives. machine learning research, data scientists, data scientist, mlops, data science, artificial intelligence, ai, machine learning false full 62 130ce5ec-43b3-4ac1-aa7c-421c823a6f50 Beyond the Model: Building Scalable, Responsible AI Systems Dushyanth shares his journey into AI, the challenges of building complex pipelines, and how to integrate responsible and ethical practices into machine learning workflows.

Key Highlights:

  • Scaling AI Systems: How to design and deploy pipelines that handle real-time inference, multimodal data, and production-level demands.
  • Model Interpretability & Explainability: Strategies for making complex models understandable and accountable.
  • Optimizing AI for Real-World Impact: Balancing performance, robustness, and human oversight in AI systems.
  • Responsible AI Practices: Embedding ethics, fairness, and transparency in machine learning workflows.

🎧 Tune in to Episode 61 to hear Dushyanth Sekhar’s insights on bridging technical innovation with responsible AI practices, and learn how to build AI systems that deliver both accuracy and real-world value.

Be sure to mark your calendars for the 9th annual DSS ATX on Feb 18, where we will focus on GENAI AND INTELLIGENT AGENTS IN THE ENTERPRISE. Join us to hear from experts on how AI is shaping the future of the enterprise. https://www.datascience.salon/austin/

As Data Science Salon celebrates 10 years the community unveils a new brand: AI Loves Data

]]> Tue, 3 Feb 2026 06:00:00 +0000 anna@formulatedby.com (Anna Anisin, Dushyanth Sekhar) https://data-science-salon-podcast.simplecast.com/episodes/beyond-the-model-building-scalable-responsible-ai-systems-DtW053Im Dushyanth shares his journey into AI, the challenges of building complex pipelines, and how to integrate responsible and ethical practices into machine learning workflows.

Key Highlights:

  • Scaling AI Systems: How to design and deploy pipelines that handle real-time inference, multimodal data, and production-level demands.
  • Model Interpretability & Explainability: Strategies for making complex models understandable and accountable.
  • Optimizing AI for Real-World Impact: Balancing performance, robustness, and human oversight in AI systems.
  • Responsible AI Practices: Embedding ethics, fairness, and transparency in machine learning workflows.

🎧 Tune in to Episode 61 to hear Dushyanth Sekhar’s insights on bridging technical innovation with responsible AI practices, and learn how to build AI systems that deliver both accuracy and real-world value.

Be sure to mark your calendars for the 9th annual DSS ATX on Feb 18, where we will focus on GENAI AND INTELLIGENT AGENTS IN THE ENTERPRISE. Join us to hear from experts on how AI is shaping the future of the enterprise. https://www.datascience.salon/austin/

As Data Science Salon celebrates 10 years the community unveils a new brand: AI Loves Data

]]> Beyond the Model: Building Scalable, Responsible AI Systems Anna Anisin, Dushyanth Sekhar 00:27:47 In this episode of the Data Science Salon Podcast, host Anna Anisin sits down with Dushyanth Sekhar, Head of AI & Data Platforms - Enterprise Data Organization at S&P Global - an AI and ML expert with experience designing and deploying scalable, production-ready AI systems across the enterprise. In this episode of the Data Science Salon Podcast, host Anna Anisin sits down with Dushyanth Sekhar, Head of AI & Data Platforms - Enterprise Data Organization at S&P Global - an AI and ML expert with experience designing and deploying scalable, production-ready AI systems across the enterprise. data structures, quantum computing, data science, artificial intelligence, ai, machine learning, gen ai false full 61 25493608-fa2d-4fdd-98fc-919871574e1e Beyond Checklists: Evaluating Conversational AI In this episode of the Data Science Salon Podcast, we sit down with Carlos Aguilar, Head of Product at Hex and former founder of Hashboard, to discuss a topic critical for every data team: how to properly evaluate AI analytics tools.

Carlos shares why traditional checklist-based evaluations fail for conversational AI and generative analytics tools, and how focusing on context, workflow, and real user testing can dramatically improve the chances of success. Drawing on his experience leading the Data Insights team at Flatiron Health, he provides practical guidance for both end-users and data teams.

Key Highlights:

  • End-User vs Data Team Evaluation: Why both perspectives are crucial for measuring AI effectiveness.
  • Context Management: How setting up reference questions ensures accurate and relevant answers.
  • Workflow & Observability: Why monitoring and iterating on AI outputs is essential for real-world success.
  • Lessons from the Field: Examples of tools that look good in demos but fail in production—and how to avoid those pitfalls.

🎧 Tune in to Episode 60 to learn how to evaluate AI analytics tools the right way and ensure your data teams deploy solutions that actually work in practice.

Be sure to mark your calendars for the 9th annual DSS ATX on Feb 18, where we will focus on GENAI AND INTELLIGENT AGENTS IN THE ENTERPRISE. Join us to hear from experts on how AI is shaping the future of the enterprise. https://www.datascience.salon/austin/

]]> Tue, 6 Jan 2026 06:00:00 +0000 anna@formulatedby.com (Carlos Aguilar, Anna Anisin) https://data-science-salon-podcast.simplecast.com/episodes/beyond-checklists-evaluating-conversational-ai-ZNClRqPR In this episode of the Data Science Salon Podcast, we sit down with Carlos Aguilar, Head of Product at Hex and former founder of Hashboard, to discuss a topic critical for every data team: how to properly evaluate AI analytics tools.

Carlos shares why traditional checklist-based evaluations fail for conversational AI and generative analytics tools, and how focusing on context, workflow, and real user testing can dramatically improve the chances of success. Drawing on his experience leading the Data Insights team at Flatiron Health, he provides practical guidance for both end-users and data teams.

Key Highlights:

  • End-User vs Data Team Evaluation: Why both perspectives are crucial for measuring AI effectiveness.
  • Context Management: How setting up reference questions ensures accurate and relevant answers.
  • Workflow & Observability: Why monitoring and iterating on AI outputs is essential for real-world success.
  • Lessons from the Field: Examples of tools that look good in demos but fail in production—and how to avoid those pitfalls.

🎧 Tune in to Episode 60 to learn how to evaluate AI analytics tools the right way and ensure your data teams deploy solutions that actually work in practice.

Be sure to mark your calendars for the 9th annual DSS ATX on Feb 18, where we will focus on GENAI AND INTELLIGENT AGENTS IN THE ENTERPRISE. Join us to hear from experts on how AI is shaping the future of the enterprise. https://www.datascience.salon/austin/

]]> Beyond Checklists: Evaluating Conversational AI Carlos Aguilar, Anna Anisin 00:22:52 In this episode of the Data Science Salon Podcast, we sit down with Carlos Aguilar, Head of Product at Hex and former founder of Hashboard, to discuss a topic critical for every data team: how to properly evaluate AI analytics tools. Have Questions or Comments? Email: events@formulatedby.com In this episode of the Data Science Salon Podcast, we sit down with Carlos Aguilar, Head of Product at Hex and former founder of Hashboard, to discuss a topic critical for every data team: how to properly evaluate AI analytics tools. Have Questions or Comments? Email: events@formulatedby.com analytics, generative ai, data science, artificial intelligence, machine learning, gen ai false full 60 cb0e502b-7696-4253-ad6b-d0b777c6b361 Reproducible EDA: Building Trustworthy Analytics Pipelines Together, Leon and Oscar share how applied EDA practices remain the backbone of trustworthy analytics pipelines in both academic and industry settings. Their discussion highlights the challenges and lessons learned from building the EDA Toolkit, and why reproducible workflows are more important than ever in the age of AI and ML.

Key Highlights:

  • Reproducible EDA: How to standardize exploratory data analysis workflows for consistent and trustworthy insights.
  • Open-Source Innovation: The design and impact of the EDA Toolkit, bridging research, healthcare, and education.
  • Best Practices for Analytics: Lessons learned from creating tools that make EDA more intuitive and scalable across projects.
  • The Future of Data Science Workflows: Why reproducibility and standardization matter in modern AI/ML pipelines.

🎧 Tune in to Episode 59 to hear Leon Shpaner and Oscar Gil’s insights on building reproducible, reliable, and effective data science workflows, and how open-source tools can transform analytics practices across domains.

Be sure to mark your calendars for the 9th annual DSS ATX on Feb 18, where we will focus on GENAI AND INTELLIGENT AGENTS IN THE ENTERPRISE. Join us to hear from experts on how AI is shaping the future of the enterprise. https://www.datascience.salon/austin/

]]> Wed, 17 Dec 2025 06:00:00 +0000 anna@formulatedby.com (Data Science Salon now AI Loves Data) https://data-science-salon-podcast.simplecast.com/episodes/reproducible-eda-building-trustworthy-analytics-pipelines-nKzHV0Vh Together, Leon and Oscar share how applied EDA practices remain the backbone of trustworthy analytics pipelines in both academic and industry settings. Their discussion highlights the challenges and lessons learned from building the EDA Toolkit, and why reproducible workflows are more important than ever in the age of AI and ML.

Key Highlights:

  • Reproducible EDA: How to standardize exploratory data analysis workflows for consistent and trustworthy insights.
  • Open-Source Innovation: The design and impact of the EDA Toolkit, bridging research, healthcare, and education.
  • Best Practices for Analytics: Lessons learned from creating tools that make EDA more intuitive and scalable across projects.
  • The Future of Data Science Workflows: Why reproducibility and standardization matter in modern AI/ML pipelines.

🎧 Tune in to Episode 59 to hear Leon Shpaner and Oscar Gil’s insights on building reproducible, reliable, and effective data science workflows, and how open-source tools can transform analytics practices across domains.

Be sure to mark your calendars for the 9th annual DSS ATX on Feb 18, where we will focus on GENAI AND INTELLIGENT AGENTS IN THE ENTERPRISE. Join us to hear from experts on how AI is shaping the future of the enterprise. https://www.datascience.salon/austin/

]]> Reproducible EDA: Building Trustworthy Analytics Pipelines Data Science Salon now AI Loves Data 00:21:46 In this episode of the Data Science Salon Podcast, we sit down with Leon Shpaner and Oscar Gil, data scientists and the creators of the open-source EDA Toolkit. Leon brings over 15 years of experience in predictive modeling across healthcare, finance, and education, while Oscar has collaborated with him to make exploratory data analysis (EDA) more intuitive, reproducible, and standardized for data science projects. Questions, comments: Let us know at info@datascience.salon In this episode of the Data Science Salon Podcast, we sit down with Leon Shpaner and Oscar Gil, data scientists and the creators of the open-source EDA Toolkit. Leon brings over 15 years of experience in predictive modeling across healthcare, finance, and education, while Oscar has collaborated with him to make exploratory data analysis (EDA) more intuitive, reproducible, and standardized for data science projects. Questions, comments: Let us know at info@datascience.salon data scientist, data structures, data collection, data science false full 59 42f3b125-e058-4217-909d-76956eced083 Ethical AI and Data Science with Kelly Vincent Kelly discusses how ethical considerations influence machine learning, NLP, and data quality, and how organizations can integrate human-centered thinking into technical decision-making. They also share insights from their upcoming book, The Friendly Guide to Data Science, aimed at making the field accessible, ethical, and practical.

Key Highlights:

  • Ethical AI in Practice: How to incorporate ethics and human-centered principles into data science projects.
  • Behavioral Economics & Decision-Making: How understanding human behavior informs AI and tech strategies.
  • Making Data Science Accessible: Kelly’s approach to mentoring, writing, and teaching the next generation of data scientists.

🎧 Tune in to Episode 58 to hear Kelly Vincent’s insights on ethical AI, data science, and technology for good.

Be sure to mark your calendars for the 7th annual DSS NYC on Dec 11, where we will focus on THE FUTURE OF APPLIED AI IN Finance and Banking. Join us to hear from experts on how AI is shaping the future of the enterprise. https://www.datascience.salon/newyork/

]]> Tue, 25 Nov 2025 06:00:00 +0000 anna@formulatedby.com (Kelly Vincent, Anna Anisin) https://data-science-salon-podcast.simplecast.com/episodes/ethical-ai-and-data-science-with-kelly-vincent-ble9s_YQ Kelly discusses how ethical considerations influence machine learning, NLP, and data quality, and how organizations can integrate human-centered thinking into technical decision-making. They also share insights from their upcoming book, The Friendly Guide to Data Science, aimed at making the field accessible, ethical, and practical.

Key Highlights:

  • Ethical AI in Practice: How to incorporate ethics and human-centered principles into data science projects.
  • Behavioral Economics & Decision-Making: How understanding human behavior informs AI and tech strategies.
  • Making Data Science Accessible: Kelly’s approach to mentoring, writing, and teaching the next generation of data scientists.

🎧 Tune in to Episode 58 to hear Kelly Vincent’s insights on ethical AI, data science, and technology for good.

Be sure to mark your calendars for the 7th annual DSS NYC on Dec 11, where we will focus on THE FUTURE OF APPLIED AI IN Finance and Banking. Join us to hear from experts on how AI is shaping the future of the enterprise. https://www.datascience.salon/newyork/

]]> Ethical AI and Data Science with Kelly Vincent Kelly Vincent, Anna Anisin 00:23:13 In this episode of the Data Science Salon Podcast, we sit down with Kelly Vincent, a data scientist at Hill’s Pet Nutrition and doctoral student at Purdue University focused on tech ethics. Kelly shares their journey from software engineering to data science, exploring the intersection of ethics, behavioral economics, and AI. Questions/Comments? Lets us know at: info@datascience.salon In this episode of the Data Science Salon Podcast, we sit down with Kelly Vincent, a data scientist at Hill’s Pet Nutrition and doctoral student at Purdue University focused on tech ethics. Kelly shares their journey from software engineering to data science, exploring the intersection of ethics, behavioral economics, and AI. Questions/Comments? Lets us know at: info@datascience.salon data scientists, data science, artificial intelligence, machine learning false full 58 44b933a8-7edc-4405-b7d4-24f4de008e57 From Code to Scale: Building SaaS and AI Products That Deliver Value Swarnendu De dives into frameworks like the SaaS Product Success Strategy™ and TechBlueprint Architecture Framework™, and shares insights on turning product ideas into execution-ready roadmaps, designing modular and scalable systems, and creating AI-powered business automation.

Key Highlights:

  • Building Scalable SaaS & AI Products: Learn Swarnendu’s approach to designing modular, cloud-native systems that meet investor expectations and real-world demands.
  • AI for Business Automation: Discover how AI can be integrated where it drives real value—automating workflows, improving decision-making, and enhancing product experiences.
  • Mentoring & Leadership: Insights into coaching tech leaders and founders, aligning technology with business goals, and accelerating team performance.
  • From Vision to Execution: Explore Swarnendu’s process for taking a concept through rapid workshops, validation, and execution-ready roadmaps.

🎧 Tune in to Episode 57  to hear how Swarnendu De is turning ideas into high-performing, scalable software products, and creating frameworks and strategies that empower teams, founders, and enterprises alike.

Be sure to mark your calendars for the 3rd annual DSS NYC on Dec 11, where we will focus on GENAI AND INTELLIGENT AGENTS IN FINANCE & BANKING. Join us to hear from experts on how AI is shaping the future of the finance, banking and insurance. https://www.datascience.salon/newyork/

]]> Wed, 12 Nov 2025 13:00:00 +0000 anna@formulatedby.com (Swarnendu De, Anna Anisin) https://data-science-salon-podcast.simplecast.com/episodes/from-code-to-scale-building-saas-and-ai-products-that-deliver-value-pai3Qk2g Swarnendu De dives into frameworks like the SaaS Product Success Strategy™ and TechBlueprint Architecture Framework™, and shares insights on turning product ideas into execution-ready roadmaps, designing modular and scalable systems, and creating AI-powered business automation.

Key Highlights:

  • Building Scalable SaaS & AI Products: Learn Swarnendu’s approach to designing modular, cloud-native systems that meet investor expectations and real-world demands.
  • AI for Business Automation: Discover how AI can be integrated where it drives real value—automating workflows, improving decision-making, and enhancing product experiences.
  • Mentoring & Leadership: Insights into coaching tech leaders and founders, aligning technology with business goals, and accelerating team performance.
  • From Vision to Execution: Explore Swarnendu’s process for taking a concept through rapid workshops, validation, and execution-ready roadmaps.

🎧 Tune in to Episode 57  to hear how Swarnendu De is turning ideas into high-performing, scalable software products, and creating frameworks and strategies that empower teams, founders, and enterprises alike.

Be sure to mark your calendars for the 3rd annual DSS NYC on Dec 11, where we will focus on GENAI AND INTELLIGENT AGENTS IN FINANCE & BANKING. Join us to hear from experts on how AI is shaping the future of the finance, banking and insurance. https://www.datascience.salon/newyork/

]]> From Code to Scale: Building SaaS and AI Products That Deliver Value Swarnendu De, Anna Anisin 00:24:18 In this episode of the Data Science Salon Podcast, we sit down with Swarnendu De, founder of AllRide Apps and Innofied Solutions, to discuss his journey from late nights debugging code to leading the architecture and delivery of 600+ scalable digital products. Swarnendu shares his experience building SaaS and AI platforms for startups and global enterprises, mentoring tech leaders, and integrating AI in ways that generate real business value. Questions? Comments? email us: info@datascience.salon In this episode of the Data Science Salon Podcast, we sit down with Swarnendu De, founder of AllRide Apps and Innofied Solutions, to discuss his journey from late nights debugging code to leading the architecture and delivery of 600+ scalable digital products. Swarnendu shares his experience building SaaS and AI platforms for startups and global enterprises, mentoring tech leaders, and integrating AI in ways that generate real business value. Questions? Comments? email us: info@datascience.salon mlops, data science, ml engineer, big data, artificial intelligence, machine learning false full 57 0ca8b151-7a91-40e2-8606-14c7f86a120b Always-On Customer Care: How AI Agents Are Transforming Support Tue, 21 Oct 2025 12:00:00 +0000 anna@formulatedby.com (Data Science Salon now AI Loves Data) https://data-science-salon-podcast.simplecast.com/episodes/always-on-customer-care-how-ai-agents-are-transforming-support-ZiTOOhKU Always-On Customer Care: How AI Agents Are Transforming Support Data Science Salon now AI Loves Data 00:32:33 In this episode of the Data Science Salon Podcast, we sit down with Nitin Kumar, Director of Data Science at Marriott International, to discuss how AI agents are transforming customer support. Nitin shares his experience designing enterprise-scale AI and Generative AI solutions across 30 global brands, creating intelligent, proactive, and human-centered customer care systems. He dives into AI-powered pipelines that monitor incoming emails, analyze sentiment and issues, and draft contextual responses for human agents to review. Beyond individual cases, these systems continuously feed real-time trend data, helping teams identify emerging issues before they become widespread. Key Highlights: -AI Agents in Customer Support: Learn how AI agents automate routine processes while empowering human agents to focus on complex interactions. -Human-in-the-Loop Design: Explore strategies for balancing AI efficiency with human oversight and empathy. -Scaling AI Solutions: Insights into LLM integration, prompt engineering, and global deployment of enterprise AI systems. 🎧 Tune in to Episode 56 to hear how Nitin Kumar is revolutionizing customer support with AI agents and Generative AI to create more efficient, empathetic, and scalable systems. Be sure to mark your calendars for the 3rd annual DSS SF on Nov 6 [FREE!] thanks to our amazing sponsors, where we will focus on GENAI AND INTELLIGENT AGENTS IN THE ENTERPRISE. Join us to hear from experts on how AI is shaping the future of the enterprise. https://www.datascience.salon/san-francisco/ In this episode of the Data Science Salon Podcast, we sit down with Nitin Kumar, Director of Data Science at Marriott International, to discuss how AI agents are transforming customer support. Nitin shares his experience designing enterprise-scale AI and Generative AI solutions across 30 global brands, creating intelligent, proactive, and human-centered customer care systems. He dives into AI-powered pipelines that monitor incoming emails, analyze sentiment and issues, and draft contextual responses for human agents to review. Beyond individual cases, these systems continuously feed real-time trend data, helping teams identify emerging issues before they become widespread. Key Highlights: -AI Agents in Customer Support: Learn how AI agents automate routine processes while empowering human agents to focus on complex interactions. -Human-in-the-Loop Design: Explore strategies for balancing AI efficiency with human oversight and empathy. -Scaling AI Solutions: Insights into LLM integration, prompt engineering, and global deployment of enterprise AI systems. 🎧 Tune in to Episode 56 to hear how Nitin Kumar is revolutionizing customer support with AI agents and Generative AI to create more efficient, empathetic, and scalable systems. Be sure to mark your calendars for the 3rd annual DSS SF on Nov 6 [FREE!] thanks to our amazing sponsors, where we will focus on GENAI AND INTELLIGENT AGENTS IN THE ENTERPRISE. Join us to hear from experts on how AI is shaping the future of the enterprise. https://www.datascience.salon/san-francisco/ false full 56 c02c6926-338b-4ebb-b789-8ea10019866a Responsible AI and the Future of Machine Learning Wed, 8 Oct 2025 05:00:00 +0000 anna@formulatedby.com (Data Science Salon now AI Loves Data) https://data-science-salon-podcast.simplecast.com/episodes/responsible-ai-and-the-future-of-machine-learning-HTrwQU_l Responsible AI and the Future of Machine Learning Data Science Salon now AI Loves Data 00:28:16 In this episode of the Data Science Salon Podcast, we sit down with Swati Tyagi, an AI/ML expert and responsible AI advocate. With deep expertise in large language models (LLMs), generative AI, and AI automation, Swati has led AI-driven innovation in FinTech, healthcare, and finance, helping organizations build scalable, ethical AI systems. Currently at JPMorgan Chase, Swati’s work focuses on automating financial applications and leveraging LLMs for real-time inferencing. Her passion for responsible AI is central to her approach, ensuring that AI systems are not only powerful but also ethical and scalable. Key Highlights: -AI and FinTech: Swati discusses her work in credit risk and predictive modeling to optimize financial decision-making and risk assessment. -Responsible AI: Insight into how to design AI systems that are both scalable and ethical, addressing challenges around bias and NLP. -AI Automation in Finance: Learn how LLMs are transforming FinTech, and how MLOps and cloud solutions play a role in scaling these applications. 🎧 Tune in to Episode 55 to hear Swati’s insights on the future of AI/ML, responsible AI, and how AI is reshaping industries like finance and healthcare. Be sure to mark your calendars for DSS SF on Nov 6, where we will focus on GENAI AND INTELLIGENT AGENTS IN THE ENTERPRISE. Join us to hear from experts on how AI is shaping the future of the enterprise. FREE COMMUNITY EVENT (space is limited) https://luma.com/dsssf In this episode of the Data Science Salon Podcast, we sit down with Swati Tyagi, an AI/ML expert and responsible AI advocate. With deep expertise in large language models (LLMs), generative AI, and AI automation, Swati has led AI-driven innovation in FinTech, healthcare, and finance, helping organizations build scalable, ethical AI systems. Currently at JPMorgan Chase, Swati’s work focuses on automating financial applications and leveraging LLMs for real-time inferencing. Her passion for responsible AI is central to her approach, ensuring that AI systems are not only powerful but also ethical and scalable. Key Highlights: -AI and FinTech: Swati discusses her work in credit risk and predictive modeling to optimize financial decision-making and risk assessment. -Responsible AI: Insight into how to design AI systems that are both scalable and ethical, addressing challenges around bias and NLP. -AI Automation in Finance: Learn how LLMs are transforming FinTech, and how MLOps and cloud solutions play a role in scaling these applications. 🎧 Tune in to Episode 55 to hear Swati’s insights on the future of AI/ML, responsible AI, and how AI is reshaping industries like finance and healthcare. Be sure to mark your calendars for DSS SF on Nov 6, where we will focus on GENAI AND INTELLIGENT AGENTS IN THE ENTERPRISE. Join us to hear from experts on how AI is shaping the future of the enterprise. FREE COMMUNITY EVENT (space is limited) https://luma.com/dsssf false full 55 c76cc482-3adb-47b6-badd-a90aba76552f Transforming the Workplace: Practical Strategies for Organizational Success with Melissa Swift Tue, 19 Aug 2025 05:00:00 +0000 anna@formulatedby.com (Data Science Salon now AI Loves Data) https://data-science-salon-podcast.simplecast.com/episodes/episode-54-transforming-the-workplace-practical-strategies-for-organizational-success-with-melissa-swift-tryCIFb6 Transforming the Workplace: Practical Strategies for Organizational Success with Melissa Swift Data Science Salon now AI Loves Data 00:23:08 In this episode of the Data Science Salon Podcast, we sit down with Melissa Swift, Founder & CEO of Anthrome Insight, and expert in organizational transformation. With over a decade of experience, Melissa partners with organizations to tackle complex challenges using data analytics, pragmatism, and a humanist approach to leadership and workplace development. Melissa is also the author of "Work Here Now: Think Like a Human and Build a Powerhouse Workplace", where she shares 90 actionable strategies for creating a workplace that fosters change, adapts to new demands, and builds resilient teams. Key Highlights: -Workplace Transformation: Learn how data analytics and humanist leadership principles are used to unlock extraordinary outcomes in the workplace. -Practical Strategies for Success: Melissa discusses 90 strategies from her book, focusing on the skills and behaviors organizations need to thrive in a changing work environment. -Solving Wicked Problems: Melissa shares how she’s helped organizations tackle complex challenges and create lasting change. -Leadership in the Future of Work: What makes a great leader in today’s rapidly evolving workplace, and how can leaders prepare for the challenges ahead? 🎧 Tune in to Episode 54 to hear how Melissa Swift is helping organizations and leaders build the workplaces of the future. Be sure to mark your calendars for DSS MIA on Sept 17, where we will focus on THE FUTURE OF APPLIED AI IN THE ENTERPRISE. Join us to hear from experts on how AI is shaping the future of the enterprise. https://www.datascience.salon/miami/ In this episode of the Data Science Salon Podcast, we sit down with Melissa Swift, Founder & CEO of Anthrome Insight, and expert in organizational transformation. With over a decade of experience, Melissa partners with organizations to tackle complex challenges using data analytics, pragmatism, and a humanist approach to leadership and workplace development. Melissa is also the author of "Work Here Now: Think Like a Human and Build a Powerhouse Workplace", where she shares 90 actionable strategies for creating a workplace that fosters change, adapts to new demands, and builds resilient teams. Key Highlights: -Workplace Transformation: Learn how data analytics and humanist leadership principles are used to unlock extraordinary outcomes in the workplace. -Practical Strategies for Success: Melissa discusses 90 strategies from her book, focusing on the skills and behaviors organizations need to thrive in a changing work environment. -Solving Wicked Problems: Melissa shares how she’s helped organizations tackle complex challenges and create lasting change. -Leadership in the Future of Work: What makes a great leader in today’s rapidly evolving workplace, and how can leaders prepare for the challenges ahead? 🎧 Tune in to Episode 54 to hear how Melissa Swift is helping organizations and leaders build the workplaces of the future. Be sure to mark your calendars for DSS MIA on Sept 17, where we will focus on THE FUTURE OF APPLIED AI IN THE ENTERPRISE. Join us to hear from experts on how AI is shaping the future of the enterprise. https://www.datascience.salon/miami/ false full 54 dcd943fd-b5ef-4728-a268-40bc41f0078c Empowering Change: Neha Mehta’s Vision for FinTech, Sustainability & Financial Inclusion Tue, 5 Aug 2025 04:00:00 +0000 anna@formulatedby.com (Data Science Salon now AI Loves Data) https://data-science-salon-podcast.simplecast.com/episodes/episode-53-empowering-change-neha-mehtas-vision-for-fintech-sustainability-financial-inclusion-_ENFwSAH Empowering Change: Neha Mehta’s Vision for FinTech, Sustainability & Financial Inclusion Data Science Salon now AI Loves Data 00:32:23 DSS Podcast Episode 53: Empowering Change: Neha Mehta’s Vision for FinTech, Sustainability & Financial Inclusion In this episode of the Data Science Salon Podcast, we sit down with Neha Mehta, a globally recognized FinTech leader, AI expert, and sustainability advocate. As the Founder and CEO of FemTech Partners, Neha has spent over 19 years transforming the financial landscape, focusing on financial inclusion, women’s empowerment, and sustainable development. She is also the author of One Stop, a bestselling book that explores the potential of Super Apps in reshaping financial services for underserved populations. In this conversation, Neha shares her journey from pioneering FinTech solutions to advancing Sustainable Development Goals (SDGs), her work in ClimateTech, and how AI can drive financial inclusivity. She also discusses her vision for the future of sustainable finance, her work with blue economy initiatives, and the impact of technology on climate action. Key Highlights: -AI for Financial Inclusion: Neha discusses how Super Apps are bridging the financial divide, enabling better access to financial services in underserved markets, and empowering women entrepreneurs. -Building Sustainable Financial Ecosystems: Learn about Neha’s approach to integrating Sustainable Development Goals (SDGs) into financial ecosystems, especially focusing on climate finance and the blue economy. -Leadership in FinTech & Sustainability: Neha shares her leadership journey and how she’s shaping a more inclusive, equitable future in FinTech and sustainable finance. -Global Impact & Mentorship: Insight into Neha’s mentorship and advocacy for fostering diversity in the tech and finance industries, and how she’s helping the next generation of leaders rise in these fields. Whether you’re an entrepreneur, FinTech innovator, or passionate about sustainability, this episode offers valuable insights into how technology is driving inclusive growth, transforming financial services, and powering climate solutions. 🎧 Tune in to Episode 53 to hear how Neha is creating impactful change at the intersection of FinTech, sustainability, and empowerment! Be sure to mark your calendars for DSS MIA on September 17, where we will focus on THE FUTURE OF APPLIED AI IN THE ENTERPRISE. Join us to hear from experts on how AI is shaping the future of applied AI. https://www.datascience.salon/miami/ DSS Podcast Episode 53: Empowering Change: Neha Mehta’s Vision for FinTech, Sustainability & Financial Inclusion In this episode of the Data Science Salon Podcast, we sit down with Neha Mehta, a globally recognized FinTech leader, AI expert, and sustainability advocate. As the Founder and CEO of FemTech Partners, Neha has spent over 19 years transforming the financial landscape, focusing on financial inclusion, women’s empowerment, and sustainable development. She is also the author of One Stop, a bestselling book that explores the potential of Super Apps in reshaping financial services for underserved populations. In this conversation, Neha shares her journey from pioneering FinTech solutions to advancing Sustainable Development Goals (SDGs), her work in ClimateTech, and how AI can drive financial inclusivity. She also discusses her vision for the future of sustainable finance, her work with blue economy initiatives, and the impact of technology on climate action. Key Highlights: -AI for Financial Inclusion: Neha discusses how Super Apps are bridging the financial divide, enabling better access to financial services in underserved markets, and empowering women entrepreneurs. -Building Sustainable Financial Ecosystems: Learn about Neha’s approach to integrating Sustainable Development Goals (SDGs) into financial ecosystems, especially focusing on climate finance and the blue economy. -Leadership in FinTech & Sustainability: Neha shares her leadership journey and how she’s shaping a more inclusive, equitable future in FinTech and sustainable finance. -Global Impact & Mentorship: Insight into Neha’s mentorship and advocacy for fostering diversity in the tech and finance industries, and how she’s helping the next generation of leaders rise in these fields. Whether you’re an entrepreneur, FinTech innovator, or passionate about sustainability, this episode offers valuable insights into how technology is driving inclusive growth, transforming financial services, and powering climate solutions. 🎧 Tune in to Episode 53 to hear how Neha is creating impactful change at the intersection of FinTech, sustainability, and empowerment! Be sure to mark your calendars for DSS MIA on September 17, where we will focus on THE FUTURE OF APPLIED AI IN THE ENTERPRISE. Join us to hear from experts on how AI is shaping the future of applied AI. https://www.datascience.salon/miami/ false full 53 25691f7b-4710-4cfb-b170-5fb7f31b5644 Agentic AI and the Future of Compliance: Revolutionizing Decision-Making and Risk Management in FinTech Tue, 22 Jul 2025 10:00:00 +0000 anna@formulatedby.com (Data Science Salon now AI Loves Data) https://data-science-salon-podcast.simplecast.com/episodes/agentic-ai-and-the-future-of-compliance-revolutionizing-decision-making-and-risk-management-in-fintech-6PduTiCj Agentic AI and the Future of Compliance: Revolutionizing Decision-Making and Risk Management in FinTech Data Science Salon now AI Loves Data 00:23:05 In this episode of the Data Science Salon Podcast, we sit down with Kalpan Dharamshi, VP at JP Morgan Chase, and a leader in Machine Learning and Cloud Architecture. Kalpan shares his journey from cloud architecture to AI-driven compliance solutions and how his work is transforming decision-making processes in the FinTech industry. Kalpan’s focus on Agentic AI—autonomous systems that can handle compliance, risk management, and real-time decision-making—has reshaped the way financial institutions manage compliance. He discusses how large language models (LLMs) and AI agents can automate and scale compliance procedures, making them proactive, accurate, and cost-effective. Key Highlights: -Agentic AI in FinTech: How Agentic AI is automating continuous monitoring and compliance in the financial services industry. -Machine Learning for Compliance: How AI can interpret unstructured data and ensure real-time policy adherence in highly dynamic industries. -The Future of AI in Decision-Making: Kalpan’s vision for the future of AI-driven decision-making and automated risk management. -Make sure to catch Kalpan at the https://appliedaisummit.org/ for free 🎧 Tune in to Episode 52 to hear how Kalpan Dharamshi is shaping the future of AI and compliance in the FinTech industry! Be sure to mark your calendars for DSS NYC on December 11, where we will focus on finance and banking—exploring the latest trends in AI and financial regulation. Join us to hear from experts on how AI is shaping the future of finance. https://www.datascience.salon/newyork/ In this episode of the Data Science Salon Podcast, we sit down with Kalpan Dharamshi, VP at JP Morgan Chase, and a leader in Machine Learning and Cloud Architecture. Kalpan shares his journey from cloud architecture to AI-driven compliance solutions and how his work is transforming decision-making processes in the FinTech industry. Kalpan’s focus on Agentic AI—autonomous systems that can handle compliance, risk management, and real-time decision-making—has reshaped the way financial institutions manage compliance. He discusses how large language models (LLMs) and AI agents can automate and scale compliance procedures, making them proactive, accurate, and cost-effective. Key Highlights: -Agentic AI in FinTech: How Agentic AI is automating continuous monitoring and compliance in the financial services industry. -Machine Learning for Compliance: How AI can interpret unstructured data and ensure real-time policy adherence in highly dynamic industries. -The Future of AI in Decision-Making: Kalpan’s vision for the future of AI-driven decision-making and automated risk management. -Make sure to catch Kalpan at the https://appliedaisummit.org/ for free 🎧 Tune in to Episode 52 to hear how Kalpan Dharamshi is shaping the future of AI and compliance in the FinTech industry! Be sure to mark your calendars for DSS NYC on December 11, where we will focus on finance and banking—exploring the latest trends in AI and financial regulation. Join us to hear from experts on how AI is shaping the future of finance. https://www.datascience.salon/newyork/ false full 52 22af1fcc-4571-4b98-a89f-4782e08dc600 Beyond the Model: Engineering Trust, Scale & Speed in AI-Powered Systems Tue, 15 Jul 2025 05:00:00 +0000 anna@formulatedby.com (Data Science Salon now AI Loves Data) https://data-science-salon-podcast.simplecast.com/episodes/beyond-the-model-engineering-trust-scale-speed-in-ai-powered-systems-_R4EHj7k Beyond the Model: Engineering Trust, Scale & Speed in AI-Powered Systems Data Science Salon now AI Loves Data 00:21:50 In this episode of the Data Science Salon Podcast, we sit down with Anusha Nerella, a seasoned technology leader and Senior Principal Software Engineer at State Street Corporation. With over a decade of experience across top-tier institutions like Barclaycard, Citibank, and USPTO, Anusha brings deep technical expertise in AI/ML automation, enterprise engineering, and scalable financial systems. In this conversation, Anusha shares her journey from software development to leading enterprise-scale AI initiatives, her work in high-frequency trading and automation frameworks, and her passion for mentoring and advancing the next generation of tech talent. Key Highlights: Engineering with Purpose: Anusha walks us through how she’s building intelligent, AI-powered automation frameworks to optimize performance and reliability in financial systems at scale. Bridging Code & Vision: A look at how her work integrates AI, DevOps, and big data architecture to deliver long-lasting, strategic impact within complex enterprise environments. Leading with Intention: Anusha discusses the role of mentorship, community involvement, and advocacy in shaping a more inclusive and innovative future in tech. The Future of AI Automation: Insight into where the industry is heading—from operationalizing machine learning to driving cross-industry transformation with intelligent systems. Whether you’re a technical founder, enterprise leader, or aspiring AI engineer, this episode offers a deep dive into how real-world AI systems are built, scaled, and delivered with precision and purpose. 🎧 Tune in to Episode 51 and get inspired by how Anusha is redefining enterprise innovation through applied AI and automation! Be sure to mark your calendars for DSS NYC on December 11, where we will focus on finance and banking—exploring the latest trends in AI and financial regulation. Join us to hear from experts on how AI is shaping the future of finance. https://www.datascience.salon/newyork/ In this episode of the Data Science Salon Podcast, we sit down with Anusha Nerella, a seasoned technology leader and Senior Principal Software Engineer at State Street Corporation. With over a decade of experience across top-tier institutions like Barclaycard, Citibank, and USPTO, Anusha brings deep technical expertise in AI/ML automation, enterprise engineering, and scalable financial systems. In this conversation, Anusha shares her journey from software development to leading enterprise-scale AI initiatives, her work in high-frequency trading and automation frameworks, and her passion for mentoring and advancing the next generation of tech talent. Key Highlights: Engineering with Purpose: Anusha walks us through how she’s building intelligent, AI-powered automation frameworks to optimize performance and reliability in financial systems at scale. Bridging Code & Vision: A look at how her work integrates AI, DevOps, and big data architecture to deliver long-lasting, strategic impact within complex enterprise environments. Leading with Intention: Anusha discusses the role of mentorship, community involvement, and advocacy in shaping a more inclusive and innovative future in tech. The Future of AI Automation: Insight into where the industry is heading—from operationalizing machine learning to driving cross-industry transformation with intelligent systems. Whether you’re a technical founder, enterprise leader, or aspiring AI engineer, this episode offers a deep dive into how real-world AI systems are built, scaled, and delivered with precision and purpose. 🎧 Tune in to Episode 51 and get inspired by how Anusha is redefining enterprise innovation through applied AI and automation! Be sure to mark your calendars for DSS NYC on December 11, where we will focus on finance and banking—exploring the latest trends in AI and financial regulation. Join us to hear from experts on how AI is shaping the future of finance. https://www.datascience.salon/newyork/ false full 51 ed5f2f88-ba2b-43ac-8e0e-bc84fa15e3d8 Architecting AI-Driven Financial Systems: Innovation at the Intersection of Fintech and Emerging Tech Tue, 24 Jun 2025 05:00:00 +0000 anna@formulatedby.com (Data Science Salon now AI Loves Data) https://data-science-salon-podcast.simplecast.com/episodes/architecting-ai-driven-financial-systems-innovation-at-the-intersection-of-fintech-and-emerging-tech-ZgA129TC Architecting AI-Driven Financial Systems: Innovation at the Intersection of Fintech and Emerging Tech Data Science Salon now AI Loves Data 00:29:07 In this episode of the Data Science Salon Podcast, we sit down with Sasibhushan Rao Chanthati, AVP and Senior Software Engineer at T. Rowe Price, where he’s building the future of finance through intelligent, scalable technologies. Sasi specializes in creating secure digital ecosystems and real-time analytics platforms that power AI-driven decision making at scale. With a background that spans research, software engineering, and cloud architecture, he’s pushing the boundaries of what’s possible at the intersection of fintech, automation, and enterprise AI. In this episode, Sasi shares insights from over a decade of experience building next-gen systems across the financial sector, his passion for ethical innovation, and what it really takes to build future-ready, inclusive AI infrastructure. Key Highlights: Sasibhushan walks us through the technical backbone of modern financial infrastructure and how AI is redefining intelligent automation. Real-world examples of building decision support systems using ServiceNow, AWS, and LLMs. Thoughts on balancing academic research with enterprise-scale engineering—and why that blend drives better innovation. Insights on the ethics and governance challenges facing enterprise AI adoption. Advice for up-and-coming engineers and researchers entering today’s fast-evolving AI landscape. This episode is a must-listen for data scientists, engineers, technical leaders, and anyone interested in how automation, AI, and cloud technologies are transforming the global financial ecosystem. 🎧 Tune in to Episode 50 to hear how Sasibhushan is shaping the future of financial systems with applied AI and inclusive innovation. In this episode of the Data Science Salon Podcast, we sit down with Sasibhushan Rao Chanthati, AVP and Senior Software Engineer at T. Rowe Price, where he’s building the future of finance through intelligent, scalable technologies. Sasi specializes in creating secure digital ecosystems and real-time analytics platforms that power AI-driven decision making at scale. With a background that spans research, software engineering, and cloud architecture, he’s pushing the boundaries of what’s possible at the intersection of fintech, automation, and enterprise AI. In this episode, Sasi shares insights from over a decade of experience building next-gen systems across the financial sector, his passion for ethical innovation, and what it really takes to build future-ready, inclusive AI infrastructure. Key Highlights: Sasibhushan walks us through the technical backbone of modern financial infrastructure and how AI is redefining intelligent automation. Real-world examples of building decision support systems using ServiceNow, AWS, and LLMs. Thoughts on balancing academic research with enterprise-scale engineering—and why that blend drives better innovation. Insights on the ethics and governance challenges facing enterprise AI adoption. Advice for up-and-coming engineers and researchers entering today’s fast-evolving AI landscape. This episode is a must-listen for data scientists, engineers, technical leaders, and anyone interested in how automation, AI, and cloud technologies are transforming the global financial ecosystem. 🎧 Tune in to Episode 50 to hear how Sasibhushan is shaping the future of financial systems with applied AI and inclusive innovation. false full 50 8659c1b0-9bed-4ef2-843d-8c42ec22a0d2 Proactive by Design: How AI Predicts and Prevents Failures Tue, 17 Jun 2025 05:00:00 +0000 anna@formulatedby.com (Data Science Salon now AI Loves Data) https://data-science-salon-podcast.simplecast.com/episodes/proactive-by-design-how-ai-predicts-and-prevents-failures-msxvv8_Q Proactive by Design: How AI Predicts and Prevents Failures Data Science Salon now AI Loves Data 00:21:06 In this episode of the Data Science Salon Podcast, we sit down with Vishnupriya Devarajulu, a Software Engineer specializing in AI- and ML-driven performance optimization for large-scale enterprise systems. With deep expertise in backend engineering, system diagnostics, and intelligent test automation, Priya is redefining how organizations build systems that don’t just respond—they anticipate. Priya walks us through her work designing adaptive frameworks that use machine learning to forecast system bottlenecks, improve latency, and optimize performance in high-stakes environments like finance. Key Highlights: Priya explains how she transforms traditional automation into self-learning, AI-powered frameworks using models like Random Forest to proactively identify and solve system issues. A deep dive into building ML-integrated performance pipelines that can adapt over time, dynamically suggest test scenarios, and drive smarter, faster, and more resilient systems. Insights into how predictive performance engineering is being applied in domains where speed and reliability are non-negotiable—and how to architect systems for it. Priya shares her perspective as a speaker and published researcher, and where she sees the future of intelligent infrastructure and AI-powered diagnostics heading next. Whether you're a systems engineer, ML practitioner, or enterprise leader exploring how AI can boost operational efficiency, this episode offers a powerful look at what happens when machine learning meets performance engineering. 🎧 Tune in to Episode 49 and discover how Priya is building the future of intelligent systems—one prediction at a time. In this episode of the Data Science Salon Podcast, we sit down with Vishnupriya Devarajulu, a Software Engineer specializing in AI- and ML-driven performance optimization for large-scale enterprise systems. With deep expertise in backend engineering, system diagnostics, and intelligent test automation, Priya is redefining how organizations build systems that don’t just respond—they anticipate. Priya walks us through her work designing adaptive frameworks that use machine learning to forecast system bottlenecks, improve latency, and optimize performance in high-stakes environments like finance. Key Highlights: Priya explains how she transforms traditional automation into self-learning, AI-powered frameworks using models like Random Forest to proactively identify and solve system issues. A deep dive into building ML-integrated performance pipelines that can adapt over time, dynamically suggest test scenarios, and drive smarter, faster, and more resilient systems. Insights into how predictive performance engineering is being applied in domains where speed and reliability are non-negotiable—and how to architect systems for it. Priya shares her perspective as a speaker and published researcher, and where she sees the future of intelligent infrastructure and AI-powered diagnostics heading next. Whether you're a systems engineer, ML practitioner, or enterprise leader exploring how AI can boost operational efficiency, this episode offers a powerful look at what happens when machine learning meets performance engineering. 🎧 Tune in to Episode 49 and discover how Priya is building the future of intelligent systems—one prediction at a time. false full 49 1c271b2d-ed46-4d8f-8f73-a8012ebff2df AI for Good: Innovating People-Centric Solutions Tue, 10 Jun 2025 05:00:00 +0000 anna@formulatedby.com (Data Science Salon now AI Loves Data) https://data-science-salon-podcast.simplecast.com/episodes/ai-for-good-innovating-people-centric-solutions-zxnh5_KO AI for Good: Innovating People-Centric Solutions Data Science Salon now AI Loves Data 00:27:45 In this episode of the Data Science Salon Podcast, we are joined by Praveena Dhanalakota, the Founder & CEO of Soopra.ai, a San Francisco-based startup that is revolutionizing industries with AI-driven solutions. Praveena is an AI expert, tech evangelist, and a passionate advocate for using technology to address real-world challenges. In this episode, she shares her inspiring journey as an entrepreneur, her mission to solve people's problems with AI, and her vision for the future of technology. Key Highlights: - Praveena talks about the human impact of AI, sharing examples of how her company is using AI to create scalable solutions that improve people's lives. - The Startup Journey: challenges and triumphs of building Soopra.ai, offering valuable insights into the startup world and the importance of solving real, practical problems with technology. - The Future of AI: thoughts on the most exciting trends in AI, where the industry is headed, and how AI can address societal challenges like healthcare, education, and sustainability. - As a female founder, Praveena offers advice and inspiration for women aspiring to make their mark in the tech world. This episode is perfect for anyone interested in the future of AI, the startup ecosystem, or how technology can be harnessed to solve pressing human challenges. 🎧 Tune in to Episode 48 and discover how AI is transforming industries and improving lives through innovative, people-centric solutions! In this episode of the Data Science Salon Podcast, we are joined by Praveena Dhanalakota, the Founder & CEO of Soopra.ai, a San Francisco-based startup that is revolutionizing industries with AI-driven solutions. Praveena is an AI expert, tech evangelist, and a passionate advocate for using technology to address real-world challenges. In this episode, she shares her inspiring journey as an entrepreneur, her mission to solve people's problems with AI, and her vision for the future of technology. Key Highlights: - Praveena talks about the human impact of AI, sharing examples of how her company is using AI to create scalable solutions that improve people's lives. - The Startup Journey: challenges and triumphs of building Soopra.ai, offering valuable insights into the startup world and the importance of solving real, practical problems with technology. - The Future of AI: thoughts on the most exciting trends in AI, where the industry is headed, and how AI can address societal challenges like healthcare, education, and sustainability. - As a female founder, Praveena offers advice and inspiration for women aspiring to make their mark in the tech world. This episode is perfect for anyone interested in the future of AI, the startup ecosystem, or how technology can be harnessed to solve pressing human challenges. 🎧 Tune in to Episode 48 and discover how AI is transforming industries and improving lives through innovative, people-centric solutions! false full 48 3b409f61-9f02-436d-ada1-0f5024b536bf AI-Driven Financial Modeling and Leading Diversity in Quantitative Analytics Tue, 3 Jun 2025 05:00:00 +0000 anna@formulatedby.com (Data Science Salon now AI Loves Data) https://data-science-salon-podcast.simplecast.com/episodes/ai-driven-financial-modeling-and-leading-diversity-in-quantitative-analytics-JDLm7F5s AI-Driven Financial Modeling and Leading Diversity in Quantitative Analytics Data Science Salon now AI Loves Data 00:18:43 In Episode 47 of the Data Science Salon Podcast, we’re joined by Akhil Khunger, the VP of Quantitative Analytics at Barclays. With over 10 years of experience in the financial industry, Akhil has a wealth of knowledge in statistical modeling, risk management, and AI-driven forecasting. He leads efforts in developing cutting-edge financial models and adapting the Basel IV framework for Risk Weighted Assets (RWA) models. Beyond his technical expertise, Akhil is also a strong advocate for diversity within his team, leading initiatives to foster inclusive and high-performance environments in Quantitative Analytics. In this episode, Akhil shares his journey from stress testing to AI-driven forecasting and discusses how he integrates diversity into his leadership practices. He also reflects on the biggest trends shaping the future of finance and AI. Key Highlights from the Episode: - AI and Financial Modeling: How Akhil integrates AI and statistical modeling in forecasting and risk management, and the role of Basel IV in shaping the future of financial analytics. - CCAR and Stress Testing: Akhil's experience in CCAR and PRA Stress Testing, and how these results are translated into actionable insights for the business. - Diversity in Tech: Akhil’s efforts to drive diversity in Quantitative Analytics, with initiatives focused on building inclusive and innovative teams. - The Future of Finance and AI: Akhil shares his thoughts on the biggest developments in quantitative finance, risk management, and AI that are set to shape the industry in the coming years. In this conversation, Akhil provides invaluable insights into the intersection of AI and financial modeling, and how diverse, high-performing teams can drive innovation and excellence in fast-evolving industries. Tune in now for expert perspectives on AI in finance, risk management, and diversity in tech. 🎧 Tune in to Episode 47 and stay ahead of the curve in finance and AI! Be sure to mark your calendars for DSS NYC on December 11, where we will focus on finance and banking—exploring the latest trends in AI and financial regulation. Join us to hear from experts on how AI is shaping the future of finance. https://www.datascience.salon/newyork/ In Episode 47 of the Data Science Salon Podcast, we’re joined by Akhil Khunger, the VP of Quantitative Analytics at Barclays. With over 10 years of experience in the financial industry, Akhil has a wealth of knowledge in statistical modeling, risk management, and AI-driven forecasting. He leads efforts in developing cutting-edge financial models and adapting the Basel IV framework for Risk Weighted Assets (RWA) models. Beyond his technical expertise, Akhil is also a strong advocate for diversity within his team, leading initiatives to foster inclusive and high-performance environments in Quantitative Analytics. In this episode, Akhil shares his journey from stress testing to AI-driven forecasting and discusses how he integrates diversity into his leadership practices. He also reflects on the biggest trends shaping the future of finance and AI. Key Highlights from the Episode: - AI and Financial Modeling: How Akhil integrates AI and statistical modeling in forecasting and risk management, and the role of Basel IV in shaping the future of financial analytics. - CCAR and Stress Testing: Akhil's experience in CCAR and PRA Stress Testing, and how these results are translated into actionable insights for the business. - Diversity in Tech: Akhil’s efforts to drive diversity in Quantitative Analytics, with initiatives focused on building inclusive and innovative teams. - The Future of Finance and AI: Akhil shares his thoughts on the biggest developments in quantitative finance, risk management, and AI that are set to shape the industry in the coming years. In this conversation, Akhil provides invaluable insights into the intersection of AI and financial modeling, and how diverse, high-performing teams can drive innovation and excellence in fast-evolving industries. Tune in now for expert perspectives on AI in finance, risk management, and diversity in tech. 🎧 Tune in to Episode 47 and stay ahead of the curve in finance and AI! Be sure to mark your calendars for DSS NYC on December 11, where we will focus on finance and banking—exploring the latest trends in AI and financial regulation. Join us to hear from experts on how AI is shaping the future of finance. https://www.datascience.salon/newyork/ false full 47 09519683-51a9-40f5-9ea5-193085ee08d3 AI-Driven Retail: Transforming Operations with Innovation and Diversity with Angie Westbrock Tue, 29 Apr 2025 16:00:00 +0000 anna@formulatedby.com (Data Science Salon now AI Loves Data) https://data-science-salon-podcast.simplecast.com/episodes/ai-driven-retail-transforming-operations-with-innovation-and-diversity-with-angie-westbrock-LnS3KYs7 AI-Driven Retail: Transforming Operations with Innovation and Diversity with Angie Westbrock Data Science Salon now AI Loves Data 00:30:34 In Episode 46 of the Data Science Salon Podcast, we explore how AI is revolutionizing the retail industry, driving operational efficiencies, and fostering innovation and diversity. This episode dives into the intersection of AI, leadership, and business strategy, featuring a discussion on how AI is transforming the way retailers optimize operations and enhance customer experiences. Our guest Angie Westbrock, CEO of Standard AI shares insights on: Harnessing AI for Retail Transformation: Learn how AI and computer vision are reshaping retail operations, providing real-time insights to optimize business performance and streamline customer experiences. - Building Diverse, High-Performance Teams: Discover strategies for cultivating diverse teams that drive innovation, solve challenges, and create meaningful solutions in fast-paced industries. - Leading with Innovation: Explore how leadership in tech requires a blend of strategic thinking, operational excellence, and a strong commitment to fostering inclusive and forward-thinking company cultures. Whether you’re interested in AI’s impact on retail or how to lead with diversity and innovation, this episode offers valuable perspectives for business leaders, AI practitioners, and anyone looking to understand the future of AI in business. In Episode 46 of the Data Science Salon Podcast, we explore how AI is revolutionizing the retail industry, driving operational efficiencies, and fostering innovation and diversity. This episode dives into the intersection of AI, leadership, and business strategy, featuring a discussion on how AI is transforming the way retailers optimize operations and enhance customer experiences. Our guest Angie Westbrock, CEO of Standard AI shares insights on: Harnessing AI for Retail Transformation: Learn how AI and computer vision are reshaping retail operations, providing real-time insights to optimize business performance and streamline customer experiences. - Building Diverse, High-Performance Teams: Discover strategies for cultivating diverse teams that drive innovation, solve challenges, and create meaningful solutions in fast-paced industries. - Leading with Innovation: Explore how leadership in tech requires a blend of strategic thinking, operational excellence, and a strong commitment to fostering inclusive and forward-thinking company cultures. Whether you’re interested in AI’s impact on retail or how to lead with diversity and innovation, this episode offers valuable perspectives for business leaders, AI practitioners, and anyone looking to understand the future of AI in business. false full 46 7ad7a4f0-66fd-4835-a012-7c3641944912 Driving Business Impact with AI: A Conversation with Maddie Daianu of Credit Karma Tue, 22 Apr 2025 05:00:00 +0000 anna@formulatedby.com (Data Science Salon now AI Loves Data) https://data-science-salon-podcast.simplecast.com/episodes/driving-business-impact-with-ai-a-conversation-with-maddie-daianu-of-credit-karma-CT7fNJbq Driving Business Impact with AI: A Conversation with Maddie Daianu of Credit Karma Data Science Salon now AI Loves Data 00:27:16 Join us for Driving Business Impact with AI: A Conversation with Maddie Daianu of Credit Karma. In this episode of the Data Science Salon Podcast, host Anna Anisin sits down with Maddie Daianu, Head of Data & AI at Credit Karma and former executive at Meta, to explore how AI, machine learning, and data-driven strategy can fuel enterprise-wide transformation. With a proven track record of driving revenue growth and innovation through AI, Maddie shares her approach to aligning ML initiatives with business outcomes, scaling high-performing teams, and influencing executive stakeholders around data-led opportunities. This conversation covers everything from monetization and predictive analytics to building a collaborative culture between technical and non-technical teams. Maddie also offers practical advice for data leaders navigating complex industries like fintech, and her perspective on the trends shaping the future of AI in business. Whether you’re leading a data team or just beginning to build one, this episode offers actionable insights on harnessing the power of AI to drive meaningful impact at scale. Tune in to gain leadership insights from one of the data industry's most influential figures and learn how you can contribute to a more diverse and inclusive data science landscape. Learn more about ML/AI in Finance at DSS NYC on May 15: https://www.datascience.salon/newyork/ Join us for Driving Business Impact with AI: A Conversation with Maddie Daianu of Credit Karma. In this episode of the Data Science Salon Podcast, host Anna Anisin sits down with Maddie Daianu, Head of Data & AI at Credit Karma and former executive at Meta, to explore how AI, machine learning, and data-driven strategy can fuel enterprise-wide transformation. With a proven track record of driving revenue growth and innovation through AI, Maddie shares her approach to aligning ML initiatives with business outcomes, scaling high-performing teams, and influencing executive stakeholders around data-led opportunities. This conversation covers everything from monetization and predictive analytics to building a collaborative culture between technical and non-technical teams. Maddie also offers practical advice for data leaders navigating complex industries like fintech, and her perspective on the trends shaping the future of AI in business. Whether you’re leading a data team or just beginning to build one, this episode offers actionable insights on harnessing the power of AI to drive meaningful impact at scale. Tune in to gain leadership insights from one of the data industry's most influential figures and learn how you can contribute to a more diverse and inclusive data science landscape. Learn more about ML/AI in Finance at DSS NYC on May 15: https://www.datascience.salon/newyork/ false full 45 46be91d6-fc4a-47ab-ad77-59738c06d6ab Beyond the Numbers: Leadership, Diversity, and Data Tue, 8 Apr 2025 05:00:00 +0000 anna@formulatedby.com (Data Science Salon now AI Loves Data) https://data-science-salon-podcast.simplecast.com/episodes/beyond-the-numbers-leadership-diversity-and-data-k8Xj879W Beyond the Numbers: Leadership, Diversity, and Data Data Science Salon now AI Loves Data 00:37:27 Join us on "Beyond the Numbers: Leadership, Diversity, and Data with Natalie Cramp, Partner at JMAN Group," where we dive deep into the intersections of data science, leadership, and advocacy for diversity. Each episode, hosted by Natalie Cramp, offers an exploration of how data-driven strategies can reshape industries and enhance decision-making processes. Natalie brings nearly two decades of experience across private, public, and third sectors, providing unique insights into mobilizing technology and people to address complex challenges. In this series, we'll uncover the transformative power of data in driving business success and societal change. Natalie will share her expertise in scaling organizations, entering new markets, and leading significant transformations. Additionally, we focus on her passionate work in promoting gender equality in healthcare through data, offering listeners actionable insights and inspiration to leverage data for impactful change. Whether you're a CEO looking to harness the potential of AI, a data professional aiming to advance in the tech field, or someone interested in the crucial role of data ethics and education, this podcast will equip you with the knowledge and perspectives needed to lead effectively in today's data-centric world. Tune in to gain leadership insights from one of the data industry's most influential figures and learn how you can contribute to a more diverse and inclusive data science landscape. Learn more about Leadership in AI/ML at DSS SEA on April 16 https://www.datascience.salon/seattle/ Join us on "Beyond the Numbers: Leadership, Diversity, and Data with Natalie Cramp, Partner at JMAN Group," where we dive deep into the intersections of data science, leadership, and advocacy for diversity. Each episode, hosted by Natalie Cramp, offers an exploration of how data-driven strategies can reshape industries and enhance decision-making processes. Natalie brings nearly two decades of experience across private, public, and third sectors, providing unique insights into mobilizing technology and people to address complex challenges. In this series, we'll uncover the transformative power of data in driving business success and societal change. Natalie will share her expertise in scaling organizations, entering new markets, and leading significant transformations. Additionally, we focus on her passionate work in promoting gender equality in healthcare through data, offering listeners actionable insights and inspiration to leverage data for impactful change. Whether you're a CEO looking to harness the potential of AI, a data professional aiming to advance in the tech field, or someone interested in the crucial role of data ethics and education, this podcast will equip you with the knowledge and perspectives needed to lead effectively in today's data-centric world. Tune in to gain leadership insights from one of the data industry's most influential figures and learn how you can contribute to a more diverse and inclusive data science landscape. Learn more about Leadership in AI/ML at DSS SEA on April 16 https://www.datascience.salon/seattle/ false full 44 96fec445-9227-4926-8377-9229e2cf852b Bridging AI and Business: Conversational AI & Communicating Data Value Tue, 25 Mar 2025 05:00:00 +0000 anna@formulatedby.com (Data Science Salon now AI Loves Data) https://data-science-salon-podcast.simplecast.com/episodes/bridging-ai-and-business-conversational-ai-communicating-data-value-w_hivq_3 Bridging AI and Business: Conversational AI & Communicating Data Value Data Science Salon now AI Loves Data 00:24:53 In this episode of the Data Science Salon Podcast, host Anna Anisin sits down with two incredible leaders driving innovation in AI and data science. First, Noelle Russell, CEO at AI Leadership Institute, shares her expertise on Conversational AI and intelligent contact centers. She discusses how companies can leverage AI-driven solutions to enhance customer experiences, streamline operations, and overcome key challenges in implementing intelligent engagement strategies. Noelle also highlights her experience leading AI initiatives at top tech companies, offering a unique perspective on the evolving role of AI in business. Next, Amarita Natt, Managing Director of Data Science at Econ One Research, dives into one of the biggest challenges in data science: communicating the value of AI and ML projects to business leaders and clients. She explores the common disconnect between technical teams and executives, sharing strategies for framing data insights in a way that drives decision-making and measurable impact. Both guests provide valuable takeaways for data professionals looking to bridge the gap between AI technology and real-world business success. Tune in for an engaging conversation on AI adoption, communication strategies, and the future of intelligent systems in business! In this episode of the Data Science Salon Podcast, host Anna Anisin sits down with two incredible leaders driving innovation in AI and data science. First, Noelle Russell, CEO at AI Leadership Institute, shares her expertise on Conversational AI and intelligent contact centers. She discusses how companies can leverage AI-driven solutions to enhance customer experiences, streamline operations, and overcome key challenges in implementing intelligent engagement strategies. Noelle also highlights her experience leading AI initiatives at top tech companies, offering a unique perspective on the evolving role of AI in business. Next, Amarita Natt, Managing Director of Data Science at Econ One Research, dives into one of the biggest challenges in data science: communicating the value of AI and ML projects to business leaders and clients. She explores the common disconnect between technical teams and executives, sharing strategies for framing data insights in a way that drives decision-making and measurable impact. Both guests provide valuable takeaways for data professionals looking to bridge the gap between AI technology and real-world business success. Tune in for an engaging conversation on AI adoption, communication strategies, and the future of intelligent systems in business! false full 43 b1d56c5c-ac2c-4720-96e7-2de123a5f0f8 AI for Good: Generative AI’s Impact & Elevating Women in STEM Tue, 18 Mar 2025 05:00:00 +0000 anna@formulatedby.com (Data Science Salon now AI Loves Data) https://data-science-salon-podcast.simplecast.com/episodes/ai-for-good-generative-ais-impact-elevating-women-in-stem-Suoipcw3 AI for Good: Generative AI’s Impact & Elevating Women in STEM Data Science Salon now AI Loves Data 00:38:25 In this episode of the Data Science Salon Podcast, host Anna Anisin sits down with two powerhouse leaders shaping the future of AI and inclusivity in tech. First, Jennetta George, SVP of AI at AlixPartners & CEO of Artificially Intelligent, shares her expertise on leveraging Generative AI for real-world impact. From forecasting market trends in finance to optimizing operations in healthcare and insurance, Jennetta dives into how LLMs are moving beyond hype into practical enterprise adoption. She also discusses strategies for navigating AI challenges and how businesses can harness AI for competitive advantage. Next, Anna is joined by Eve Psalti, Principal Group Program Manager at Microsoft and a passionate advocate for women in STEM. Eve highlights the barriers women still face in tech and the steps needed to foster a more inclusive industry. She shares insights on mentorship, hiring practices, and the importance of diverse leadership in AI and data science. Both guests provide invaluable perspectives on the evolving AI landscape and the role of diversity in driving innovation. Tune in to explore the intersection of AI, business transformation, and inclusivity in tech! In this episode of the Data Science Salon Podcast, host Anna Anisin sits down with two powerhouse leaders shaping the future of AI and inclusivity in tech. First, Jennetta George, SVP of AI at AlixPartners & CEO of Artificially Intelligent, shares her expertise on leveraging Generative AI for real-world impact. From forecasting market trends in finance to optimizing operations in healthcare and insurance, Jennetta dives into how LLMs are moving beyond hype into practical enterprise adoption. She also discusses strategies for navigating AI challenges and how businesses can harness AI for competitive advantage. Next, Anna is joined by Eve Psalti, Principal Group Program Manager at Microsoft and a passionate advocate for women in STEM. Eve highlights the barriers women still face in tech and the steps needed to foster a more inclusive industry. She shares insights on mentorship, hiring practices, and the importance of diverse leadership in AI and data science. Both guests provide invaluable perspectives on the evolving AI landscape and the role of diversity in driving innovation. Tune in to explore the intersection of AI, business transformation, and inclusivity in tech! false full 42 627f9756-c040-4f1d-ba1d-2a259bc055e6 Building Data Excellence at Nordstrom: Scaling Standards & Measurement for Impact Mon, 17 Feb 2025 17:00:00 +0000 anna@formulatedby.com (Data Science Salon now AI Loves Data) https://data-science-salon-podcast.simplecast.com/episodes/building-data-excellence-at-nordstrom-scaling-standards-measurement-for-impact-ORwIntjx Building Data Excellence at Nordstrom: Scaling Standards & Measurement for Impact Data Science Salon now AI Loves Data 00:34:50 In this episode of the Data Science Salon Podcast, host Anna Anisin sits down with two data leaders from Nordstrom to explore how organizations can build a culture of technical excellence and measurement in data science. First, Gina Schmalzle, Principal Data Scientist at Nordstrom, shares her experience leading the Technical Excellence Initiative within the company’s data science and analytics organization. She discusses the challenges of scaling data teams, the importance of setting standards for efficiency and collaboration, and how MLOps and feature stores can streamline data science workflows. Gina provides practical insights into creating high-quality, scalable data solutions that drive business impact. Next, Kevin Haynes, former Program Manager at Nordstrom, takes us into the world of "Eating Your Own Dog Food"—Building a Culture of Measurement for Data Products. He explores why internal metrics are essential for validating and improving data-driven solutions and how data teams can adopt a product mindset when developing internal tools. Kevin also shares his approach to fostering an engaging, high-impact team culture while ensuring that measurement and accountability remain at the core of data initiatives. Both guests offer interesting insights into building sustainable, high-performing data organizations in today’s evolving AI and data landscape. Tune in to learn actionable strategies from two data leaders shaping the future of AI and analytics. In this episode of the Data Science Salon Podcast, host Anna Anisin sits down with two data leaders from Nordstrom to explore how organizations can build a culture of technical excellence and measurement in data science. First, Gina Schmalzle, Principal Data Scientist at Nordstrom, shares her experience leading the Technical Excellence Initiative within the company’s data science and analytics organization. She discusses the challenges of scaling data teams, the importance of setting standards for efficiency and collaboration, and how MLOps and feature stores can streamline data science workflows. Gina provides practical insights into creating high-quality, scalable data solutions that drive business impact. Next, Kevin Haynes, former Program Manager at Nordstrom, takes us into the world of "Eating Your Own Dog Food"—Building a Culture of Measurement for Data Products. He explores why internal metrics are essential for validating and improving data-driven solutions and how data teams can adopt a product mindset when developing internal tools. Kevin also shares his approach to fostering an engaging, high-impact team culture while ensuring that measurement and accountability remain at the core of data initiatives. Both guests offer interesting insights into building sustainable, high-performing data organizations in today’s evolving AI and data landscape. Tune in to learn actionable strategies from two data leaders shaping the future of AI and analytics. false full 41 c2d8e96b-fcfa-4d22-bd08-f09e85d0fcdf Exploring the Past, Present, and Future of AI/ML Tue, 28 Jan 2025 17:00:00 +0000 anna@formulatedby.com (Data Science Salon now AI Loves Data) https://data-science-salon-podcast.simplecast.com/episodes/exploring-the-past-present-and-future-of-ai-ml-s_UbJl6T Exploring the Past, Present, and Future of AI/ML Data Science Salon now AI Loves Data 00:40:47 In this episode of the Data Science Salon Podcast, host Anna Anisin sits down with two influential leaders in AI and data science to discuss their experiences, challenges, and insights into the evolving landscape of the industry. First, Fatma Tarlaci, Chief Technology Officer at Rastegar Capital, shares her journey as an AI engineering leader, discussing the intersection of technical execution and strategic leadership. She explores the importance of responsible AI, open-source contributions, and aligning technical teams with business goals to drive impactful solutions. Fatma provides actionable insights on fostering innovation while maintaining ethical AI development. Next, Brent Schneeman, Director of AI and Software Engineering at PMG, brings his unique perspective on building high-performing interdisciplinary teams and navigating the evolving expectations in AI and machine learning. He shares lessons learned from his journey, insights into stakeholder collaboration, and the importance of cultivating a “test and learn” culture within organizations. Both guests provide invaluable perspectives on leading AI initiatives, overcoming industry challenges, and staying ahead in an era of rapid technological change. Tune in to gain practical knowledge and inspiration from their experiences. In this episode of the Data Science Salon Podcast, host Anna Anisin sits down with two influential leaders in AI and data science to discuss their experiences, challenges, and insights into the evolving landscape of the industry. First, Fatma Tarlaci, Chief Technology Officer at Rastegar Capital, shares her journey as an AI engineering leader, discussing the intersection of technical execution and strategic leadership. She explores the importance of responsible AI, open-source contributions, and aligning technical teams with business goals to drive impactful solutions. Fatma provides actionable insights on fostering innovation while maintaining ethical AI development. Next, Brent Schneeman, Director of AI and Software Engineering at PMG, brings his unique perspective on building high-performing interdisciplinary teams and navigating the evolving expectations in AI and machine learning. He shares lessons learned from his journey, insights into stakeholder collaboration, and the importance of cultivating a “test and learn” culture within organizations. Both guests provide invaluable perspectives on leading AI initiatives, overcoming industry challenges, and staying ahead in an era of rapid technological change. Tune in to gain practical knowledge and inspiration from their experiences. false full 40 f7e66daf-6281-4b41-9a8e-464583fe3fbc 2025 Predictions: The Future of AI, LLMs, and Data Science Tue, 14 Jan 2025 17:00:00 +0000 anna@formulatedby.com (Data Science Salon now AI Loves Data) https://data-science-salon-podcast.simplecast.com/episodes/2025-predictions-the-future-of-ai-llms-and-data-science-WlO0zwGO 2025 Predictions: The Future of AI, LLMs, and Data Science Data Science Salon now AI Loves Data 00:18:47 In this episode, Anna Anisin, Founder of Data Science Salon, and Tyler Carmody, Head of Event Operations, catch up on everything we missed over the past few weeks. They dive into exciting developments in AI, including how it’s transforming scientific research, solving complex problems, and revolutionizing business tools. They also discuss predictions for 2025—what trends we expect to see in AI, LLMs, and generative AI, and how these technologies are shaping industries across the globe. Plus, don’t miss exciting news about the upcoming DSS ATX event on February 19-20, with a special discount code DSSPODCASTATX for 20% off your registration. We’re also looking for startups to join our showcase—check the application link in the description! Tune in for insights and trends you won’t want to miss as we head into the new year! Help Displaced LA Families: https://tinyurl.com/3ftz96wf Help Educators: https://tinyurl.com/6ce6nj26 Essential Aid for Palisades Community: https://gofund.me/c1ca2235 Village School Relief: https://tinyurl.com/3vvjwneu In this episode, Anna Anisin, Founder of Data Science Salon, and Tyler Carmody, Head of Event Operations, catch up on everything we missed over the past few weeks. They dive into exciting developments in AI, including how it’s transforming scientific research, solving complex problems, and revolutionizing business tools. They also discuss predictions for 2025—what trends we expect to see in AI, LLMs, and generative AI, and how these technologies are shaping industries across the globe. Plus, don’t miss exciting news about the upcoming DSS ATX event on February 19-20, with a special discount code DSSPODCASTATX for 20% off your registration. We’re also looking for startups to join our showcase—check the application link in the description! Tune in for insights and trends you won’t want to miss as we head into the new year! Help Displaced LA Families: https://tinyurl.com/3ftz96wf Help Educators: https://tinyurl.com/6ce6nj26 Essential Aid for Palisades Community: https://gofund.me/c1ca2235 Village School Relief: https://tinyurl.com/3vvjwneu false full 39 aa4caac5-d086-41df-95af-d1a4bf0f841e Data-Driven Excellence: AI and Analytics in Action with Matthew Denesuk & Jaime Russ Tue, 10 Sep 2024 12:04:22 +0000 anna@formulatedby.com (Data Science Salon now AI Loves Data) https://data-science-salon-podcast.simplecast.com/episodes/data-driven-excellence-ai-and-analytics-in-action-with-matthew-denesuk-jaime-russ-O4CeMYEv Data-Driven Excellence: AI and Analytics in Action with Matthew Denesuk & Jaime Russ Data Science Salon now AI Loves Data 00:32:41 In this DSS Podcast we chat with Matthew Denesuk, SVP of Data Analytics & AI at Royal Caribbean Group. Matthew shares his insights on leveraging a Center of Excellence model to drive data-driven strategies across the organization. Tune in to discover how this approach can transform enterprise business processes using AI, analytics, and data science! We’re also excited to welcome Jaime Russ, former Principal Data Scientist at Ryder System. Jaime brings a fresh perspective on data science, focusing on integrating advanced analytics and machine learning models into traditionally held concepts. Tune in as she explores the application of machine learning in corporate finance and its fascinating parallels to fleet management. In this DSS Podcast we chat with Matthew Denesuk, SVP of Data Analytics & AI at Royal Caribbean Group. Matthew shares his insights on leveraging a Center of Excellence model to drive data-driven strategies across the organization. Tune in to discover how this approach can transform enterprise business processes using AI, analytics, and data science! We’re also excited to welcome Jaime Russ, former Principal Data Scientist at Ryder System. Jaime brings a fresh perspective on data science, focusing on integrating advanced analytics and machine learning models into traditionally held concepts. Tune in as she explores the application of machine learning in corporate finance and its fascinating parallels to fleet management. false full 38 1c29f664-6fd9-41c6-88f4-855d2efcf85a AI in Action: From Machine Learning Interpretability to Cybersecurity with Serg Masís and Nirmal Budhathoki Tue, 6 Aug 2024 12:19:09 +0000 anna@formulatedby.com (Data Science Salon now AI Loves Data) https://data-science-salon-podcast.simplecast.com/episodes/ai-in-action-from-machine-learning-interpretability-to-cybersecurity-with-serg-masis-and-nirmal-budhathoki-8LxQDKBT AI in Action: From Machine Learning Interpretability to Cybersecurity with Serg Masís and Nirmal Budhathoki Data Science Salon now AI Loves Data 00:25:37 In this DSS Podcast, Anna Anisin welcomes Serg Masís, Climate and Agronomic Data Scientist at Syngenta. Serg, an expert in machine learning interpretability and responsible AI, shares his diverse background and journey into data science. He discusses the challenges of building fair and reliable ML models, emphasizing the importance of interpretability and trust in AI. Serg also talks into his latest book, "Interpretable Machine Learning with Python," and provides valuable insights for data scientists striving to create more transparent and effective AI solutions. In another compelling episode, Anna sits down with Nirmal Budhathoki, Senior Data Scientist at Microsoft. Nirmal, who has extensive experience at VMware Carbon Black and Wells Fargo, focuses on the intersection of AI and cybersecurity. He shares his journey into security data science, discussing the unique challenges and critical importance of applying AI to enhance cybersecurity measures. Nirmal highlights the pressing need for AI in this field, practical use cases, and the complexities involved in integrating AI with security practices, offering a valuable perspective for professionals navigating this dynamic landscape. In this DSS Podcast, Anna Anisin welcomes Serg Masís, Climate and Agronomic Data Scientist at Syngenta. Serg, an expert in machine learning interpretability and responsible AI, shares his diverse background and journey into data science. He discusses the challenges of building fair and reliable ML models, emphasizing the importance of interpretability and trust in AI. Serg also talks into his latest book, "Interpretable Machine Learning with Python," and provides valuable insights for data scientists striving to create more transparent and effective AI solutions. In another compelling episode, Anna sits down with Nirmal Budhathoki, Senior Data Scientist at Microsoft. Nirmal, who has extensive experience at VMware Carbon Black and Wells Fargo, focuses on the intersection of AI and cybersecurity. He shares his journey into security data science, discussing the unique challenges and critical importance of applying AI to enhance cybersecurity measures. Nirmal highlights the pressing need for AI in this field, practical use cases, and the complexities involved in integrating AI with security practices, offering a valuable perspective for professionals navigating this dynamic landscape. false full 37 fab715c1-2476-434b-85d6-91d7462ce5c9 AI at the Crossroads: Bias, Diversity, and Scalability with Boshika Tara and Dr. June Andrews Tue, 23 Jul 2024 15:29:07 +0000 anna@formulatedby.com (Data Science Salon now AI Loves Data) https://data-science-salon-podcast.simplecast.com/episodes/ai-at-the-crossroads-bias-diversity-and-scalability-with-boshika-tara-and-dr-june-andrews-OasXiB26 AI at the Crossroads: Bias, Diversity, and Scalability with Boshika Tara and Dr. June Andrews Data Science Salon now AI Loves Data 00:27:48 In this week's DSSPodcast, Anna had a conversation with Boshika Tara, Technical Machine Learning Product Manager at H&M Group. Boshika brings over 7 years of experience in technical product development, engineering, and building large-scale ML systems in NLP and Computer Vision. In this episode, she dives into the critical issue of bias in AI, discussing various types of biases in machine learning, how to detect them, and the importance of creating more equitable teams with diverse representation to mitigate these biases. Additionally, Anna had the pleasure of hosting Dr. June Andrews, the Founder of Lat Long Labs. Dr. Andrews shares her incredible journey from leading the Style Discovery team at Stitch Fix to her role as a Tech Lead at LinkedIn. She discusses the complexities of scaling and transforming AI projects, particularly in predicting consumer preferences and enhancing product discovery. In this week's DSSPodcast, Anna had a conversation with Boshika Tara, Technical Machine Learning Product Manager at H&M Group. Boshika brings over 7 years of experience in technical product development, engineering, and building large-scale ML systems in NLP and Computer Vision. In this episode, she dives into the critical issue of bias in AI, discussing various types of biases in machine learning, how to detect them, and the importance of creating more equitable teams with diverse representation to mitigate these biases. Additionally, Anna had the pleasure of hosting Dr. June Andrews, the Founder of Lat Long Labs. Dr. Andrews shares her incredible journey from leading the Style Discovery team at Stitch Fix to her role as a Tech Lead at LinkedIn. She discusses the complexities of scaling and transforming AI projects, particularly in predicting consumer preferences and enhancing product discovery. false full 36 083fda08-a163-48e1-96e5-12cd19472067 Elevating Computer Vision and Female Voices with Alex Levinson and Sheila Beladinejad Tue, 9 Jul 2024 17:44:32 +0000 anna@formulatedby.com (Data Science Salon now AI Loves Data) https://data-science-salon-podcast.simplecast.com/episodes/elevating-computer-vision-and-female-voices-with-alex-levinson-and-sheila-beladinejad-7DSPQkU5 Elevating Computer Vision and Female Voices with Alex Levinson and Sheila Beladinejad Data Science Salon now AI Loves Data 00:21:00 In this episode of the DSS Podcast, Anna Anisin introduces two powerhouse guests in the realms of AI and robotics. First, Anna welcomes Alex, Principal Algorithms/AI Engineer at Elbit Systems of America, based in Miami. Alex shares her journey into the field of AI, particularly computer vision, and discusses common use cases, pitfalls, and success stories in sourcing and improving data for computer vision models. She also offers valuable recommendations for data scientists starting out in the field and highlights an exciting trend in AI that she's currently following. Next, Anna introduces Sheila Beladinejad, President of Women in AI & Robotics. Sheila talks about the network she built in Germany, dedicated to fostering gender-inclusive, ethical, and responsible AI and robotics solutions. She highlights the importance of creating such a network and the positive impact it has had on the AI and robotics community. In this episode of the DSS Podcast, Anna Anisin introduces two powerhouse guests in the realms of AI and robotics. First, Anna welcomes Alex, Principal Algorithms/AI Engineer at Elbit Systems of America, based in Miami. Alex shares her journey into the field of AI, particularly computer vision, and discusses common use cases, pitfalls, and success stories in sourcing and improving data for computer vision models. She also offers valuable recommendations for data scientists starting out in the field and highlights an exciting trend in AI that she's currently following. Next, Anna introduces Sheila Beladinejad, President of Women in AI & Robotics. Sheila talks about the network she built in Germany, dedicated to fostering gender-inclusive, ethical, and responsible AI and robotics solutions. She highlights the importance of creating such a network and the positive impact it has had on the AI and robotics community. false full 35 7851935c-1fa8-4c97-ac08-b5e9ac426164 Using AI & Machine Learning to Develop Better Healthcare Experiences with Sumayah Rahman and Vaibhav Verdhan Mon, 24 Jun 2024 12:33:08 +0000 anna@formulatedby.com (Data Science Salon now AI Loves Data) https://data-science-salon-podcast.simplecast.com/episodes/using-ai-machine-learning-to-develop-better-healthcare-experiences-with-sumayah-rahman-and-vaibhav-verdhan-_yB4Lkiy Using AI & Machine Learning to Develop Better Healthcare Experiences with Sumayah Rahman and Vaibhav Verdhan Data Science Salon now AI Loves Data 00:21:25 In this episode of the Data Science Salon Podcast, host Anna Anisin sits down with two leading experts in the ML/AI healthcare industry. First, Sumayah Rahman, Director of Data Science - Machine Learning and Infrastructure at Cedar, discusses optimizing the patient experience to make healthcare more affordable and accessible. She explains how ML-powered discounts can benefit both patients and providers, sharing practical examples of using data to enhance patient experiences and highlighting the transformative impact of AI/ML in healthcare. Next, Vaibhav Verdhan, Analytics Leader at AstraZeneca, dives into the role of computer vision in healthcare and his favorite technologies in the healthcare analytics space. He discusses how advanced analytics are driving innovation at AstraZeneca by developing, deploying, and maintaining decision support capabilities. Both guests provide valuable insights into how AI and ML are revolutionizing healthcare, offering listeners practical knowledge and inspiration. In this episode of the Data Science Salon Podcast, host Anna Anisin sits down with two leading experts in the ML/AI healthcare industry. First, Sumayah Rahman, Director of Data Science - Machine Learning and Infrastructure at Cedar, discusses optimizing the patient experience to make healthcare more affordable and accessible. She explains how ML-powered discounts can benefit both patients and providers, sharing practical examples of using data to enhance patient experiences and highlighting the transformative impact of AI/ML in healthcare. Next, Vaibhav Verdhan, Analytics Leader at AstraZeneca, dives into the role of computer vision in healthcare and his favorite technologies in the healthcare analytics space. He discusses how advanced analytics are driving innovation at AstraZeneca by developing, deploying, and maintaining decision support capabilities. Both guests provide valuable insights into how AI and ML are revolutionizing healthcare, offering listeners practical knowledge and inspiration. false full 34 95897e6b-adef-47a4-966e-bc3c4bfebd77 Lessons Learned from Applying Data Science in Finance and a Deep Dive into Drift with Mabu Manaileng and Adam Lieberman Mon, 17 Jun 2024 13:44:51 +0000 anna@formulatedby.com (Data Science Salon now AI Loves Data) https://data-science-salon-podcast.simplecast.com/episodes/lessons-learned-from-applying-data-science-in-finance-and-a-deep-dive-into-drift-with-mabu-manaileng-and-adam-lieberman-30_gdwt4 Lessons Learned from Applying Data Science in Finance and a Deep Dive into Drift with Mabu Manaileng and Adam Lieberman Data Science Salon now AI Loves Data 00:20:44 In this episode, Anna sits down with two leaders in the finance industry, exploring the forefront of AI and ML innovations. First, we have Mabu Manaileng, Lead Data Scientist at Standard Bank Group. Mabu shares his journey and current role, highlights the challenges of applied data science in the financial sector, and discusses the transformative impact of AI on banking in the coming years. Next, we welcome Adam Lieberman, Head of AI and ML at Finastra. Adam defines the concept of drift, discusses statistical measures to quantify it, and provides strategies for maintaining model health, ensuring that models continue to serve users' needs effectively. In this episode, Anna sits down with two leaders in the finance industry, exploring the forefront of AI and ML innovations. First, we have Mabu Manaileng, Lead Data Scientist at Standard Bank Group. Mabu shares his journey and current role, highlights the challenges of applied data science in the financial sector, and discusses the transformative impact of AI on banking in the coming years. Next, we welcome Adam Lieberman, Head of AI and ML at Finastra. Adam defines the concept of drift, discusses statistical measures to quantify it, and provides strategies for maintaining model health, ensuring that models continue to serve users' needs effectively. false full 33 508d8f18-96a7-4e94-96f3-31c7efea7196 Leveraging Statistical Models and ESG to Grow Your Business with Laura Gabrysiak and Rochelle March Mon, 10 Jun 2024 12:44:05 +0000 anna@formulatedby.com (Data Science Salon now AI Loves Data) https://data-science-salon-podcast.simplecast.com/episodes/leveraging-statistical-models-and-esg-to-grow-your-business-with-laura-gabrysiak-and-rochelle-march-qSSv2uoT Leveraging Statistical Models and ESG to Grow Your Business with Laura Gabrysiak and Rochelle March Data Science Salon now AI Loves Data 00:36:20 In this episode, Anna sits down with two leaders in the finance industry, exploring the forefront of AI, ML, and ESG innovations. First, let's welcome Laura Gabrysiak, Data Science Leader at Visa. Laura develops statistical models and decision analytics tools that enable Visa clients to transform massive amounts of data into actionable ML models and AI implementations. She's also passionate about fostering the local data science community in Miami as the Founder of R-Ladies Miami. In this conversation, they dive into the future of ML/AI in financial services and the impactful work being done with Code Art to promote diversity in tech. Next, we have Rochelle March, former Head of ESG Product at Dun & Bradstreet. Rochelle specializes in impact analysis related to carbon, water, and the Sustainable Development Goals, and applies machine learning to ESG products. She also teaches data and analytics at Bard College’s MBA program, sits on the advisory board for USL Technology, Inc., and mentors fellows in the Environmental Defense Fund’s Climate Corps program. Since recording this episode, Rochelle has started her own company, People Places Words Actions. In our discussion, we explore her journey in ESG innovation and analytics, why ESG data is crucial for responsible investment decisions, and how it drives sustainable business practices. Tune in to learn from these industry thought leaders and gain insights into the cutting-edge applications of AI and ESG data in the finance sector. In this episode, Anna sits down with two leaders in the finance industry, exploring the forefront of AI, ML, and ESG innovations. First, let's welcome Laura Gabrysiak, Data Science Leader at Visa. Laura develops statistical models and decision analytics tools that enable Visa clients to transform massive amounts of data into actionable ML models and AI implementations. She's also passionate about fostering the local data science community in Miami as the Founder of R-Ladies Miami. In this conversation, they dive into the future of ML/AI in financial services and the impactful work being done with Code Art to promote diversity in tech. Next, we have Rochelle March, former Head of ESG Product at Dun & Bradstreet. Rochelle specializes in impact analysis related to carbon, water, and the Sustainable Development Goals, and applies machine learning to ESG products. She also teaches data and analytics at Bard College’s MBA program, sits on the advisory board for USL Technology, Inc., and mentors fellows in the Environmental Defense Fund’s Climate Corps program. Since recording this episode, Rochelle has started her own company, People Places Words Actions. In our discussion, we explore her journey in ESG innovation and analytics, why ESG data is crucial for responsible investment decisions, and how it drives sustainable business practices. Tune in to learn from these industry thought leaders and gain insights into the cutting-edge applications of AI and ESG data in the finance sector. false full 32 ed785c5e-7f4e-4e0b-9f52-04ddb589a982 FinTech Insights: AI Innovations, Privacy Strategies, and Synthetic Data with Harry Mendell & Supreet Kaur Mon, 3 Jun 2024 13:50:15 +0000 anna@formulatedby.com (Data Science Salon now AI Loves Data) https://data-science-salon-podcast.simplecast.com/episodes/fintech-insights-ai-innovations-privacy-strategies-and-synthetic-data-with-harry-mendell-supreet-kaur-QA4_Squ2 FinTech Insights: AI Innovations, Privacy Strategies, and Synthetic Data with Harry Mendell & Supreet Kaur Data Science Salon now AI Loves Data 00:32:06 In this episode, Anna sits down with two distinguished leaders in the ML/AI finance industry. First, we have Harry Mendell, Technology Group Data Architect at the Federal Reserve Bank of New York, who brings over 30 years of expertise in FinTech. Harry shares compelling stories and discusses emerging trends in the finance sector. Following Harry, Supreet Kaur, AVP at Morgan Stanley and product owner for various AI products, joins the conversation. Supreet provides insights into the use of synthetic data to protect customer privacy in FinTech, ensuring informed decision-making. This deep dive into synthetic data highlights its growing importance in the industry. In this episode, Anna sits down with two distinguished leaders in the ML/AI finance industry. First, we have Harry Mendell, Technology Group Data Architect at the Federal Reserve Bank of New York, who brings over 30 years of expertise in FinTech. Harry shares compelling stories and discusses emerging trends in the finance sector. Following Harry, Supreet Kaur, AVP at Morgan Stanley and product owner for various AI products, joins the conversation. Supreet provides insights into the use of synthetic data to protect customer privacy in FinTech, ensuring informed decision-making. This deep dive into synthetic data highlights its growing importance in the industry. false full 31 0d9c2dfa-4569-474f-b8fb-3cb001db0207 Context Matters: Generative AI, the spectrum of worldviews, and understanding propaganda's appeal Ben Dubow studied the Middle East during his undergrad and took a job tracking terrorist groups.  After a brief stint at a large tech company, he launched Omelas, a company that combines AI and subject matter expertise to deliver intelligence to national security professionals.In today's episode, our Senior Content Advisor Q McCallum caught up with Ben to learn more about what Omelas is up to and how the company applies AI and data analysis to its mission.Along the way they explore the value of data in context; why it's important to ask the right questions of the right data, and not just the whole pool; the power of involving humans in the data pipeline; and what it takes to do NLP and NER at scale.  The two also talk about the impact of generative AI on democracy and authoritarianism.  A topic which, interestingly enough, holds lessons for corporations that plan to release AI chatbots.Links mentioned in this episode:

]]> Tue, 24 Oct 2023 15:41:55 +0000 anna@formulatedby.com (Data Science Salon now AI Loves Data) https://data-science-salon-podcast.simplecast.com/episodes/context-matters-generative-ai-the-spectrum-of-worldviews-and-understanding-propagandas-appeal-nB1HVyIG Ben Dubow studied the Middle East during his undergrad and took a job tracking terrorist groups.  After a brief stint at a large tech company, he launched Omelas, a company that combines AI and subject matter expertise to deliver intelligence to national security professionals.In today's episode, our Senior Content Advisor Q McCallum caught up with Ben to learn more about what Omelas is up to and how the company applies AI and data analysis to its mission.Along the way they explore the value of data in context; why it's important to ask the right questions of the right data, and not just the whole pool; the power of involving humans in the data pipeline; and what it takes to do NLP and NER at scale.  The two also talk about the impact of generative AI on democracy and authoritarianism.  A topic which, interestingly enough, holds lessons for corporations that plan to release AI chatbots.Links mentioned in this episode:

]]> Context Matters: Generative AI, the spectrum of worldviews, and understanding propaganda's appeal Data Science Salon now AI Loves Data 00:50:45 Ben Dubow of Omelas joins us to talk about data in context, NLP/NER at scale, and the impact of generative AI on democracy + authoritarianism. Ben Dubow of Omelas joins us to talk about data in context, NLP/NER at scale, and the impact of generative AI on democracy + authoritarianism. false full 30 b3e38a7e-ac05-4887-8dbe-3be99b2899ee When companies try to "sprinkle some AI" on a product

If you've been in the data game long enough, you've probably seen this before: a stakeholder or product owner approaches you with a project that's 95% done, and they'd like you to … "sprinkle some AI on it."  They've heard that this "AI" thing can be useful so they want some of it in their latest effort.Data scientist-turned-product person Noelle Saldana has experienced the "sprinkle some AI on it" request more times than she'd care to remember.  Our Senior Content Advisor Q McCallum met up with Noelle to explore this phenomenon.  How does this happen? (Hint: "corporate FOMO.")  What should you do when stakeholders insist on implementing AI that isn't actually going to help?  What about when your data scientist peers seem like they're doing this for the sake of "résumé-driven development?"Ultimately, the pair work through the bigger issue: how do you make peace with companies throwing money at AI like this? And how can these companies use this approach to their advantage?As a bonus, Noelle shares how she made the move from a data scientist role into product management.  If this path sounds interesting to you, take a listen.

]]> Wed, 17 May 2023 14:02:19 +0000 anna@formulatedby.com (Data Science Salon now AI Loves Data) https://data-science-salon-podcast.simplecast.com/episodes/when-companies-try-to-sprinkle-some-ai-on-a-product-Z0Cv4vK0

If you've been in the data game long enough, you've probably seen this before: a stakeholder or product owner approaches you with a project that's 95% done, and they'd like you to … "sprinkle some AI on it."  They've heard that this "AI" thing can be useful so they want some of it in their latest effort.Data scientist-turned-product person Noelle Saldana has experienced the "sprinkle some AI on it" request more times than she'd care to remember.  Our Senior Content Advisor Q McCallum met up with Noelle to explore this phenomenon.  How does this happen? (Hint: "corporate FOMO.")  What should you do when stakeholders insist on implementing AI that isn't actually going to help?  What about when your data scientist peers seem like they're doing this for the sake of "résumé-driven development?"Ultimately, the pair work through the bigger issue: how do you make peace with companies throwing money at AI like this? And how can these companies use this approach to their advantage?As a bonus, Noelle shares how she made the move from a data scientist role into product management.  If this path sounds interesting to you, take a listen.

]]> When companies try to "sprinkle some AI" on a product Data Science Salon now AI Loves Data 00:58:18 Data scientist-turned-product person Noelle Saldana has experienced the "sprinkle some AI on it" request more times than she'd care to remember. Our Senior Content Advisor Q McCallum met up with Noelle to explore this phenomenon. How does this happen? (Hint: "corporate FOMO.") What should you do when stakeholders insist on implementing AI that isn't actually going to help? What about when your data scientist peers seem like they're doing this for the sake of "résumé-driven development?" Data scientist-turned-product person Noelle Saldana has experienced the "sprinkle some AI on it" request more times than she'd care to remember. Our Senior Content Advisor Q McCallum met up with Noelle to explore this phenomenon. How does this happen? (Hint: "corporate FOMO.") What should you do when stakeholders insist on implementing AI that isn't actually going to help? What about when your data scientist peers seem like they're doing this for the sake of "résumé-driven development?" false full 29 279bd208-204c-4af9-b09b-223d92f335e5 Building data products with Solomon Kahn Sometimes the most valuable data IN your company ... is the data LEAVING your company.That's Solomon Kahn's view on data products, as well as the premise behind his latest venture: Delivery Layer.For this episode, our Senior Content Advisor Q McCallum reached out to Solomon to check in on the new startup, and to tap his expertise in the world of data products.Solomon's been at this a while.  He's run high-revenue data products in some notable places, including Nielsen.  Over the years he's learned a lot and we're excited for him to share some of that hard-earned knowledge here on the show.In this extended conversation, the two explore: the reasons why building a data product is different (and, in many ways, more difficult) than building traditional software products; how the people involved can impact the outcome; why a good sense of risk management can make all the difference; and what purple cars have to do with all of this. (No, seriously.  Purple cars.)Along the way, the pair talk about the early days of the data field, and how much it has changed.

]]> Tue, 7 Mar 2023 19:40:00 +0000 anna@formulatedby.com (Data Science Salon now AI Loves Data) https://data-science-salon-podcast.simplecast.com/episodes/building-data-products-with-solomon-kahn-Yk_JW7Or Sometimes the most valuable data IN your company ... is the data LEAVING your company.That's Solomon Kahn's view on data products, as well as the premise behind his latest venture: Delivery Layer.For this episode, our Senior Content Advisor Q McCallum reached out to Solomon to check in on the new startup, and to tap his expertise in the world of data products.Solomon's been at this a while.  He's run high-revenue data products in some notable places, including Nielsen.  Over the years he's learned a lot and we're excited for him to share some of that hard-earned knowledge here on the show.In this extended conversation, the two explore: the reasons why building a data product is different (and, in many ways, more difficult) than building traditional software products; how the people involved can impact the outcome; why a good sense of risk management can make all the difference; and what purple cars have to do with all of this. (No, seriously.  Purple cars.)Along the way, the pair talk about the early days of the data field, and how much it has changed.

]]> Building data products with Solomon Kahn Data Science Salon now AI Loves Data 01:21:47 Sometimes the most valuable data IN your company ... is the data LEAVING your company. That's Solomon Kahn's view on data products, as well as the premise behind his latest venture: Delivery Layer. For this episode, our Senior Content Advisor Q McCallum reached out to Solomon to check in on the new startup, and to tap his expertise in the world of data products. Solomon's been at this a while. He's run high-revenue data products in some notable places, including Nielsen. Over the years he's learned a lot and we're excited for him to share some of that hard-earned knowledge here on the show. In this extended conversation, the two explore: the reasons why building a data product is different (and, in many ways, more difficult) than building traditional software products; how the people involved can impact the outcome; why a good sense of risk management can make all the difference; and what purple cars have to do with all of this. (No, seriously. Purple cars.) Along the way, the pair talk about the early days of the data field, and how much it has changed. Sometimes the most valuable data IN your company ... is the data LEAVING your company. That's Solomon Kahn's view on data products, as well as the premise behind his latest venture: Delivery Layer. For this episode, our Senior Content Advisor Q McCallum reached out to Solomon to check in on the new startup, and to tap his expertise in the world of data products. Solomon's been at this a while. He's run high-revenue data products in some notable places, including Nielsen. Over the years he's learned a lot and we're excited for him to share some of that hard-earned knowledge here on the show. In this extended conversation, the two explore: the reasons why building a data product is different (and, in many ways, more difficult) than building traditional software products; how the people involved can impact the outcome; why a good sense of risk management can make all the difference; and what purple cars have to do with all of this. (No, seriously. Purple cars.) Along the way, the pair talk about the early days of the data field, and how much it has changed. false full 28 3e56b7e6-1888-401d-855f-04e49dbfac84 Probabilistic Thinking with James "JD" Long In this episode, James and Q explore:

  • The ideas of risk and uncertainty.
  • What is "probabilistic thinking" and why is it important for data scientists?
  • The career progression of a data analyst, and what it means to develop statistical acumen.
  • Thinking in terms of distributions, and thinking in different moments of a distribution.
  • Seeing BI, AI, and simulation in terms of punctuation.  (No, seriously.)
  • How to bridge the gap into thinking probabilistically

And, just a reminder: James only speaks for himself in this episode and he does not represent his employer.Links mentioned during our discussion:

The list of books James mentioned:

  • Thinking in Bets (Annie Duke)
  • Fortune's Formula (Poundstone)
  • The Lady Tasting Tea (Salsburg)
  • Fooled by Randomness (Taleb)
]]> Wed, 26 Oct 2022 18:10:27 +0000 anna@formulatedby.com (Data Science Salon now AI Loves Data) https://data-science-salon-podcast.simplecast.com/episodes/probabilistic-thinking-with-james-jd-long-7COO23NK In this episode, James and Q explore:

  • The ideas of risk and uncertainty.
  • What is "probabilistic thinking" and why is it important for data scientists?
  • The career progression of a data analyst, and what it means to develop statistical acumen.
  • Thinking in terms of distributions, and thinking in different moments of a distribution.
  • Seeing BI, AI, and simulation in terms of punctuation.  (No, seriously.)
  • How to bridge the gap into thinking probabilistically

And, just a reminder: James only speaks for himself in this episode and he does not represent his employer.Links mentioned during our discussion:

The list of books James mentioned:

  • Thinking in Bets (Annie Duke)
  • Fortune's Formula (Poundstone)
  • The Lady Tasting Tea (Salsburg)
  • Fooled by Randomness (Taleb)
]]> Probabilistic Thinking with James "JD" Long Data Science Salon now AI Loves Data 01:17:00 Our show host and Senior Content Advisor, Q McCallum, has been thinking a lot about what he calls "moving beyond the point estimate" in ML modeling. That usually starts with seeing the world in terms of statistical distributions, and running simulations to get a more robust picture of a model's results. When he had questions, he reached out to his old friend James "JD" Long for answers. James is a self-described "agricultural economist, quant, stochastic modeler, and cocktail party host" who does a lot of work in R, Python, and AWS. Through his work in the reinsurance field he has developed deep knowledge of simulations and probabilistic thinking, as well as an ability to explain these topics in plain language. Our show host and Senior Content Advisor, Q McCallum, has been thinking a lot about what he calls "moving beyond the point estimate" in ML modeling. That usually starts with seeing the world in terms of statistical distributions, and running simulations to get a more robust picture of a model's results. When he had questions, he reached out to his old friend James "JD" Long for answers. James is a self-described "agricultural economist, quant, stochastic modeler, and cocktail party host" who does a lot of work in R, Python, and AWS. Through his work in the reinsurance field he has developed deep knowledge of simulations and probabilistic thinking, as well as an ability to explain these topics in plain language. false full 27 3c39e540-bdc3-4996-81c5-adf9be495473 The roles of economists in data science, with Dr. Amar Natt We've all heard the term "economist," sure. But exactly what does and economist do? And as economics is a very data-driven field, where does their work intersect with data science, machine learning, and AI?

To answer that question, Senior Content Advisor Q McCallum spoke with Amar Natt, PhD. She's an economist at Econ One Research, and her work focuses on advanced analytics and predictive modeling. Does that sound like ML to you? Well, Amar explains that it's similar in some ways, different in others. From there, she tells us about techniques economists can learn from data scientists, and what data scientists can pick up from econ. (Hint: "causal inference." You heard it here first.) You can find Amar online:

Be part of the conversation and connect with the data science community at DSS Miami Hybrid on September 21, 2022.

Book your ticket now.

]]> Wed, 17 Aug 2022 16:31:34 +0000 anna@formulatedby.com (Data Science Salon now AI Loves Data) https://data-science-salon-podcast.simplecast.com/episodes/the-roles-of-economists-in-data-science-with-dr-amar-natt-1i_I627S We've all heard the term "economist," sure. But exactly what does and economist do? And as economics is a very data-driven field, where does their work intersect with data science, machine learning, and AI?

To answer that question, Senior Content Advisor Q McCallum spoke with Amar Natt, PhD. She's an economist at Econ One Research, and her work focuses on advanced analytics and predictive modeling. Does that sound like ML to you? Well, Amar explains that it's similar in some ways, different in others. From there, she tells us about techniques economists can learn from data scientists, and what data scientists can pick up from econ. (Hint: "causal inference." You heard it here first.) You can find Amar online:

Be part of the conversation and connect with the data science community at DSS Miami Hybrid on September 21, 2022.

Book your ticket now.

]]> The roles of economists in data science, with Dr. Amar Natt Data Science Salon now AI Loves Data 00:43:20 We've all heard the term "economist," sure. But exactly what does and economist do? And as economics is a very data-driven field, where does their work intersect with data science, machine learning, and AI? To answer that question, Senior Content Advisor Q McCallum spoke with Amar Natt, PhD. She's an economist at Econ One Research, and her work focuses on advanced analytics and predictive modeling. Does that sound like ML to you? Well, Amar explains that it's similar in some ways, different in others. From there, she tells us about techniques economists can learn from data scientists, and what data scientists can pick up from econ. (Hint: "causal inference." You heard it here first.) We've all heard the term "economist," sure. But exactly what does and economist do? And as economics is a very data-driven field, where does their work intersect with data science, machine learning, and AI? To answer that question, Senior Content Advisor Q McCallum spoke with Amar Natt, PhD. She's an economist at Econ One Research, and her work focuses on advanced analytics and predictive modeling. Does that sound like ML to you? Well, Amar explains that it's similar in some ways, different in others. From there, she tells us about techniques economists can learn from data scientists, and what data scientists can pick up from econ. (Hint: "causal inference." You heard it here first.) false full 26 72e4854a-044b-4895-be05-8ecbaa58eb97 ML at The Home Depot with Pat Woowong: The Falloff Model and Lead Scoring When people think about The Home Depot, they probably think more about lumber
and tile than they do ML models.  Sure, there is plenty of lumber.  But machine learning also plays a key role in the business, in places that customers can see as well as the behind-the-scenes operations.Senior Content Advisor Q McCallum met up with Pat Woowong, Director of Data Science at The Home Depot, to explore how the company mixes their very rich dataset with domain knowledge to employ machine learning deep inside the business.  To frame this, he walked me through the Falloff model and Lead scoring, two projects that his team deployed to address the unique challenges of a company that handles both retail and services.During our conversation, we discussed: understanding where models fit into the bigger business picture; using expert domain knowledge to drive feature selection and feature engineering; the value of process; and, to top it off, what it's like to work at The Home Depot.Other places to find Pat:

Be part of the conversation and connect with the data science community at DSS Miami Hybrid on September 21, 2022.

Book your ticket now.

]]> Wed, 20 Jul 2022 17:33:13 +0000 anna@formulatedby.com (Data Science Salon now AI Loves Data) https://data-science-salon-podcast.simplecast.com/episodes/ml-at-the-home-depot-with-pat-woowong-the-falloff-model-and-lead-scoring-jm9thVHR When people think about The Home Depot, they probably think more about lumber
and tile than they do ML models.  Sure, there is plenty of lumber.  But machine learning also plays a key role in the business, in places that customers can see as well as the behind-the-scenes operations.Senior Content Advisor Q McCallum met up with Pat Woowong, Director of Data Science at The Home Depot, to explore how the company mixes their very rich dataset with domain knowledge to employ machine learning deep inside the business.  To frame this, he walked me through the Falloff model and Lead scoring, two projects that his team deployed to address the unique challenges of a company that handles both retail and services.During our conversation, we discussed: understanding where models fit into the bigger business picture; using expert domain knowledge to drive feature selection and feature engineering; the value of process; and, to top it off, what it's like to work at The Home Depot.Other places to find Pat:

Be part of the conversation and connect with the data science community at DSS Miami Hybrid on September 21, 2022.

Book your ticket now.

]]> ML at The Home Depot with Pat Woowong: The Falloff Model and Lead Scoring Data Science Salon now AI Loves Data 01:05:56 When people think about The Home Depot, they probably think more about lumber and tile than they do ML models. Sure, there is plenty of lumber. But machine learning also plays a key role in the business, in places that customers can see as well as the behind-the-scenes operations. Senior Content Advisor Q McCallum met up with Pat Woowong, Director of Data Science at The Home Depot, to explore how the company mixes their very rich dataset with domain knowledge to employ machine learning deep inside the business. To frame this, he walked me through the Falloff model and Lead scoring, two projects that his team deployed to address the unique challenges of a company that handles both retail and services. During our conversation, we discussed: understanding where models fit into the bigger business picture; using expert domain knowledge to drive feature selection and feature engineering; the value of process; and, to top it off, what it's like to work at The Home Depot. When people think about The Home Depot, they probably think more about lumber and tile than they do ML models. Sure, there is plenty of lumber. But machine learning also plays a key role in the business, in places that customers can see as well as the behind-the-scenes operations. Senior Content Advisor Q McCallum met up with Pat Woowong, Director of Data Science at The Home Depot, to explore how the company mixes their very rich dataset with domain knowledge to employ machine learning deep inside the business. To frame this, he walked me through the Falloff model and Lead scoring, two projects that his team deployed to address the unique challenges of a company that handles both retail and services. During our conversation, we discussed: understanding where models fit into the bigger business picture; using expert domain knowledge to drive feature selection and feature engineering; the value of process; and, to top it off, what it's like to work at The Home Depot. false full 25 7fd465a7-2a09-4039-92fd-105f3cac8f20 Coffee Chat: Inspiring ML Use Cases in Retail Delivering Measurable Impact Thu, 26 May 2022 16:45:23 +0000 anna@formulatedby.com (Data Science Salon now AI Loves Data) https://data-science-salon-podcast.simplecast.com/episodes/coffee-chat-dss-virtual-may-2022-OqRU0G3P Coffee Chat: Inspiring ML Use Cases in Retail Delivering Measurable Impact Data Science Salon now AI Loves Data 00:34:09 This episode is a coffee chat recording from DSS Virtual in May 2022. Charles Irizarry (Phygital) and Ankita Mangal (P&G) share in war stories of ML use cases they use in retail and eCommerce scenarios, brokering data, and protecting the important principles of data ethics and privacy. Ankita shares the digital transformation journey that P&G undertook, her growth together with P&G, and some of the incredible technologies P&G has developed to better serve their customers world wide. This episode is a coffee chat recording from DSS Virtual in May 2022. Charles Irizarry (Phygital) and Ankita Mangal (P&G) share in war stories of ML use cases they use in retail and eCommerce scenarios, brokering data, and protecting the important principles of data ethics and privacy. Ankita shares the digital transformation journey that P&G undertook, her growth together with P&G, and some of the incredible technologies P&G has developed to better serve their customers world wide. false full 24 82330029-964b-43ba-b255-4039921053f8 Data Science and Data Engineering in the Federal Space with Dr. Pragyansmita Nayak A lot of data scientists work in the private sector: finance, adtech, retail, and all that.  Today's guest offers her perspective on what it means to do data work in the federal space.In this conversation, our Senior Content Advisor Q McCallum spoke with Dr. Pragyansmita Nayak, Chief Data Scientist at Hitachi Vantara Federal.  They explored how different federal agencies use data and how they share datasets with each other. They also talked about how to measure operational efficiency, when you can't rely on metrics like "profit." And, the big question: should we release t-shirts that read "just give me my AI solution!" ?You can find Pragyan online:

The book Q mentioned is Army of None, by Paul Scharre.

]]> Thu, 19 May 2022 21:46:30 +0000 anna@formulatedby.com (Data Science Salon now AI Loves Data) https://data-science-salon-podcast.simplecast.com/episodes/data-science-and-data-engineering-in-the-federal-space-with-dr-pragyansmita-nayak-ylL2_MUd A lot of data scientists work in the private sector: finance, adtech, retail, and all that.  Today's guest offers her perspective on what it means to do data work in the federal space.In this conversation, our Senior Content Advisor Q McCallum spoke with Dr. Pragyansmita Nayak, Chief Data Scientist at Hitachi Vantara Federal.  They explored how different federal agencies use data and how they share datasets with each other. They also talked about how to measure operational efficiency, when you can't rely on metrics like "profit." And, the big question: should we release t-shirts that read "just give me my AI solution!" ?You can find Pragyan online:

The book Q mentioned is Army of None, by Paul Scharre.

]]> Data Science and Data Engineering in the Federal Space with Dr. Pragyansmita Nayak Data Science Salon now AI Loves Data 00:54:44 A lot of data scientists work in the private sector: finance, adtech, retail, and all that. Today's guest offers her perspective on what it means to do data work in the federal space. In this conversation, our Senior Content Advisor Q McCallum spoke with Dr. Pragyansmita Nayak, Chief Data Scientist at Hitachi Vantara Federal. They explored how different federal agencies use data and how they share datasets with each other. They also talked about how to measure operational efficiency, when you can't rely on metrics like "profit." And, the big question: should we release t-shirts that read "just give me my AI solution!" ? A lot of data scientists work in the private sector: finance, adtech, retail, and all that. Today's guest offers her perspective on what it means to do data work in the federal space. In this conversation, our Senior Content Advisor Q McCallum spoke with Dr. Pragyansmita Nayak, Chief Data Scientist at Hitachi Vantara Federal. They explored how different federal agencies use data and how they share datasets with each other. They also talked about how to measure operational efficiency, when you can't rely on metrics like "profit." And, the big question: should we release t-shirts that read "just give me my AI solution!" ? false full 23 3450eacb-e590-470e-898a-b301d7870aa0 Software Development Skills in ML/AI Thu, 5 May 2022 21:50:12 +0000 anna@formulatedby.com (Data Science Salon now AI Loves Data) https://data-science-salon-podcast.simplecast.com/episodes/software-development-skills-in-ml-ai-asOmSt7H Software Development Skills in ML/AI Data Science Salon now AI Loves Data 00:29:33 In this episode, our Senior Content Advisor Q McCallum met up with Murium Iqbal from Etsy. They spoke about an important skill for data scientists: software development! Data scientists write a lot of code, sure, but few of them come from a formal software dev background. That can lead them to struggle with slow, buggy code that ultimately holds back the company's ML efforts. Want to write cleaner, more performant code? Looking for ways to make those model deployments more reproducible? Listen to Murium and Q explore topics such as writing tests, using Docker to isolate dependencies, and learning best practices from your software developer teammates. In this episode, our Senior Content Advisor Q McCallum met up with Murium Iqbal from Etsy. They spoke about an important skill for data scientists: software development! Data scientists write a lot of code, sure, but few of them come from a formal software dev background. That can lead them to struggle with slow, buggy code that ultimately holds back the company's ML efforts. Want to write cleaner, more performant code? Looking for ways to make those model deployments more reproducible? Listen to Murium and Q explore topics such as writing tests, using Docker to isolate dependencies, and learning best practices from your software developer teammates. false full 22 8f08af54-424c-4576-81d7-a8e2eaad7bf9 Coffee Chat: Model Interpretability And How To Create Trust In AI Products Wed, 27 Apr 2022 20:09:09 +0000 anna@formulatedby.com (Data Science Salon now AI Loves Data) https://data-science-salon-podcast.simplecast.com/episodes/coffee-chat-model-interpretability-and-how-to-create-trust-in-ai-products-rfuqwLsH Coffee Chat: Model Interpretability And How To Create Trust In AI Products Data Science Salon now AI Loves Data 00:46:18 This episode is a recording of the panel conversation at the virtual Data Science Salon in April 2022, which focused on AI & machine learning applications in the enterprise. Charles Irizarry (CEO & Co-Founder at Strata.ai) had the chance to talk to Amarita Natt (Managing Director, Data Science at Econ One Research), Preethi Raghavan (VP, Data Science Practice Lead at Fidelity Investments) and Serg Masís (Climate and Agronomic Data Scientist at Syngenta) about the important topic of model interpretability and how to create trust in AI products. This episode is a recording of the panel conversation at the virtual Data Science Salon in April 2022, which focused on AI & machine learning applications in the enterprise. Charles Irizarry (CEO & Co-Founder at Strata.ai) had the chance to talk to Amarita Natt (Managing Director, Data Science at Econ One Research), Preethi Raghavan (VP, Data Science Practice Lead at Fidelity Investments) and Serg Masís (Climate and Agronomic Data Scientist at Syngenta) about the important topic of model interpretability and how to create trust in AI products. false full 21 4b323ece-28a7-4c90-b1c2-6c0f9a3c0453 Coffee Chat: DSS Hybrid Miami 2022 Charles Irizarry, CEO & Co-Founder at Strata.ai had the chance to talk to Nirmal Budhathoki, Senior Data Scientist at VMware Carbon Black and Moody Hadi, Group Manager - New Product Development & Financial Engineering at S&P Global. Tune in to hear about ML techniques they are using in their current roles, tools to put ML into production, model explainability, and future trends.

]]> Wed, 2 Mar 2022 21:57:43 +0000 anna@formulatedby.com (Charles Irizarry, Nirmal Budhathoki, Moody Hadi) https://data-science-salon-podcast.simplecast.com/episodes/coffee-chat-dss-hybrid-miami-2022-5PnpdLpn Charles Irizarry, CEO & Co-Founder at Strata.ai had the chance to talk to Nirmal Budhathoki, Senior Data Scientist at VMware Carbon Black and Moody Hadi, Group Manager - New Product Development & Financial Engineering at S&P Global. Tune in to hear about ML techniques they are using in their current roles, tools to put ML into production, model explainability, and future trends.

]]> Coffee Chat: DSS Hybrid Miami 2022 Charles Irizarry, Nirmal Budhathoki, Moody Hadi 00:44:23 This episode is a recording of the coffee chat at the hybrid Data Science Salon Miami, which focused on AI & machine learning applications in the enterprise. This episode is a recording of the coffee chat at the hybrid Data Science Salon Miami, which focused on AI & machine learning applications in the enterprise. mlops, artificial intelligence, machine learning false full 20 c129b7bf-ebff-4e29-bfe6-f61aa67955d9 Communal Computing and AI with Chris Butler (2/2) In the previous episode, our Senior Content Advisor Q McCallum met with product manager Chris Butler to explore the role of uncertainty and how it relates to AI product management.  That conversation sets the stage for Chris and Q to talk about communal computing today.

Chris starts by explaining what shared, AI-backed devices mean for data collection, analysis, and regulation. After that, Chris and Q explore important questions such as: What are some challenges in getting communal computing devices to coordinate?  How do social norms mix with assumptions made by the ML models behind these devices?  What do we lose when we use data lakes? How do product managers and machine learning engineers interact on these kinds of projects? What do communal computing devices have in common with software developers on shared platforms?And, most importantly: what does all of this have to do with the film Napoleon Dynamite ...?

]]> Thu, 13 Jan 2022 14:48:51 +0000 anna@formulatedby.com (Q McCallum, Chris Butler) https://data-science-salon-podcast.simplecast.com/episodes/communal-computing-and-ai-with-chris-butler-2-2-qGEhlmF1 In the previous episode, our Senior Content Advisor Q McCallum met with product manager Chris Butler to explore the role of uncertainty and how it relates to AI product management.  That conversation sets the stage for Chris and Q to talk about communal computing today.

Chris starts by explaining what shared, AI-backed devices mean for data collection, analysis, and regulation. After that, Chris and Q explore important questions such as: What are some challenges in getting communal computing devices to coordinate?  How do social norms mix with assumptions made by the ML models behind these devices?  What do we lose when we use data lakes? How do product managers and machine learning engineers interact on these kinds of projects? What do communal computing devices have in common with software developers on shared platforms?And, most importantly: what does all of this have to do with the film Napoleon Dynamite ...?

]]> Communal Computing and AI with Chris Butler (2/2) Q McCallum, Chris Butler 01:08:04 In the previous episode, our Senior Content Advisor Q McCallum met with product manager Chris Butler to explore the role of uncertainty and how it relates to AI product management. That conversation sets the stage for Chris and Q to talk about communal computing today. In the previous episode, our Senior Content Advisor Q McCallum met with product manager Chris Butler to explore the role of uncertainty and how it relates to AI product management. That conversation sets the stage for Chris and Q to talk about communal computing today. ml, cognizant, communal computing, data collection, data science, artificial intelligence, ai, machine learning false full 19 4cdb68db-fda5-4039-8af4-02ee403ee7bc Coffee Chat: DSS Virtual Finance & Technology 2021 Formulated.by’s Senior Content Advisor, Q McCallum, caught up with Linda Liu (Hyrecar) and Giacomo Vianello (Cape Analytics).  Our guests explored the techniques and tools for the various data projects they are running, some of the challenges of working with geospatial data, and how their companies approach data-related research efforts.

]]> Thu, 16 Dec 2021 05:35:48 +0000 anna@formulatedby.com (Q McCallum, Linda Liu, Giacomo Vianello) https://data-science-salon-podcast.simplecast.com/episodes/coffee-chat-dss-virtual-finance-technology-2021-n5B41obm Formulated.by’s Senior Content Advisor, Q McCallum, caught up with Linda Liu (Hyrecar) and Giacomo Vianello (Cape Analytics).  Our guests explored the techniques and tools for the various data projects they are running, some of the challenges of working with geospatial data, and how their companies approach data-related research efforts.

]]> Coffee Chat: DSS Virtual Finance & Technology 2021 Q McCallum, Linda Liu, Giacomo Vianello 00:59:40 Today’s episode is a recording of the Coffee Chat from our Data Science Salon Virtual Finance & Technology. The Data Science Salon for Finance and Technology is the only industry conference that brings together specialists in the finance and technology data science fields to educate each other, illuminate best practices, and innovate new solutions in a casual atmosphere. Today’s episode is a recording of the Coffee Chat from our Data Science Salon Virtual Finance & Technology. The Data Science Salon for Finance and Technology is the only industry conference that brings together specialists in the finance and technology data science fields to educate each other, illuminate best practices, and innovate new solutions in a casual atmosphere. fintech, data science salon, cape analytics, geospatial data, data science, hyrecar, ai, machine learning false full 18 7d0900cd-8165-460e-a58a-b445e9a8e41c AI, Product, and Uncertainty with Chris Butler (1/2) This discussion also explores the context around which we collect data, polysocial reality, design individualism, and contextual integrity.  (Yes, we covered a lot of ground in just 45 minutes.)

Because of our tight schedule, Chris and Q had to stop before they could get to their second topic.  That’s why Chris will be back in the next episode to talk about communal computing and what that means for AI.            

bio: Chris Butler is a product manager, writer, and speaker with over 20 years of product management leadership at Microsoft, Waze, KAYAK, and Facebook Reality Labs. He facilitates critical decision making for teams that build new and innovative products and created techniques like Empathy Mapping for the Machine and Confusion Mapping to create cross-team alignment while building AI products. 

He is now Assistant Vice President, Head of Product Operations, at Cognizant where he PM’s the PM experience.Learn more about Chris and his work through his Linkedin, Twitter, by reading some of his articles on Medium or watching some of his past talks on YouTube.

]]> Thu, 4 Nov 2021 13:52:08 +0000 anna@formulatedby.com (Q McCallum, Chris Butler) https://data-science-salon-podcast.simplecast.com/episodes/ai-product-and-uncertainty-with-chris-butler-XJrNFRKN This discussion also explores the context around which we collect data, polysocial reality, design individualism, and contextual integrity.  (Yes, we covered a lot of ground in just 45 minutes.)

Because of our tight schedule, Chris and Q had to stop before they could get to their second topic.  That’s why Chris will be back in the next episode to talk about communal computing and what that means for AI.            

bio: Chris Butler is a product manager, writer, and speaker with over 20 years of product management leadership at Microsoft, Waze, KAYAK, and Facebook Reality Labs. He facilitates critical decision making for teams that build new and innovative products and created techniques like Empathy Mapping for the Machine and Confusion Mapping to create cross-team alignment while building AI products. 

He is now Assistant Vice President, Head of Product Operations, at Cognizant where he PM’s the PM experience.Learn more about Chris and his work through his Linkedin, Twitter, by reading some of his articles on Medium or watching some of his past talks on YouTube.

]]> AI, Product, and Uncertainty with Chris Butler (1/2) Q McCallum, Chris Butler 00:47:05 Welcome to our first two-part episode! Our Senior Content Advisor, Q McCallum, caught up with product manager Chris Butler to talk about the intersection of AI and product. In particular, Chris’s two decades of professional experience have taught him a lot about the role of uncertainty: we dig deep into what that term really means, how much data scientists need to concern themselves with uncertainty in their work, and how this relates to a company’s values. Welcome to our first two-part episode! Our Senior Content Advisor, Q McCallum, caught up with product manager Chris Butler to talk about the intersection of AI and product. In particular, Chris’s two decades of professional experience have taught him a lot about the role of uncertainty: we dig deep into what that term really means, how much data scientists need to concern themselves with uncertainty in their work, and how this relates to a company’s values. ml, cognizant, communal computing, data collection, data science, artificial intelligence, ai, machine learning false full 17 10afdf07-13b0-4c59-8241-94c12dc58df5 Coffee Chat: DSSe Virtual 2021 Formulated.by’s Senior Content Advisor, Q McCallum, caught up with Vidhi Chugh (Walmart), Piyanka Jain (Aryng), and Tempest van Schaik (Microsoft).  Our guests explored the impact of the Covid-19 pandemic on hiring and retention, then shifted to a discussion on finding and serving as a mentor.

]]> Thu, 16 Sep 2021 00:28:29 +0000 anna@formulatedby.com (Vidhi Chugh, Tempest van Schaik, Q McCallum, Piyanka Jain) https://data-science-salon-podcast.simplecast.com/episodes/coffee-chat-dsse-virtual-2021-GT5OrdUw Formulated.by’s Senior Content Advisor, Q McCallum, caught up with Vidhi Chugh (Walmart), Piyanka Jain (Aryng), and Tempest van Schaik (Microsoft).  Our guests explored the impact of the Covid-19 pandemic on hiring and retention, then shifted to a discussion on finding and serving as a mentor.

]]> Coffee Chat: DSSe Virtual 2021 Vidhi Chugh, Tempest van Schaik, Q McCallum, Piyanka Jain 00:54:21 Today’s episode is a recording of the Coffee Chat from our Data Science Salon Elevate series. Elevate is our unique women focused virtual conference that includes BIPOC, members of the LGBTQIA+, and other underrepresented groups. Today’s episode is a recording of the Coffee Chat from our Data Science Salon Elevate series. Elevate is our unique women focused virtual conference that includes BIPOC, members of the LGBTQIA+, and other underrepresented groups. walmart, mentor, women in data, aryng, data science salon, dsse, microsoft, elevate, ai false full 16 9d9faa75-e48d-42f5-b5a6-a3c6cbb85a70 Analytics vs. Data Science vs. ML Research: Economist Sonali Syngal Shares Her View Formulatedby's Senior Content Advisor, Q McCallum, met up with Sonali Syngal to explore these questions.  Sonali is currently a data scientist at MasterCard and is about to join the team at Expedia.  She came to data science from the rather uncommon entry point of economics. In this episode we see that her career path has given her key insights on how to join this field and what are the differences between the various roles therein.(Some listeners may recognize Sonali's voice from a previous episode: she spoke at Data Science Salon in December 2020, where she also joined us for our Coffee Chat.  You can check out that episode to learn more about Sonali's take on ML/AI in the world of fintech.)

]]> Thu, 27 May 2021 23:12:58 +0000 anna@formulatedby.com (Sonali Syngal - Senior Scientist at Mastercard, Q McCallum - Senior Content Advisor at Formulatedby) https://data-science-salon-podcast.simplecast.com/episodes/analytics-vs-data-science-vs-ml-research-an-economist-shares-her-view-xETtnPq3 Formulatedby's Senior Content Advisor, Q McCallum, met up with Sonali Syngal to explore these questions.  Sonali is currently a data scientist at MasterCard and is about to join the team at Expedia.  She came to data science from the rather uncommon entry point of economics. In this episode we see that her career path has given her key insights on how to join this field and what are the differences between the various roles therein.(Some listeners may recognize Sonali's voice from a previous episode: she spoke at Data Science Salon in December 2020, where she also joined us for our Coffee Chat.  You can check out that episode to learn more about Sonali's take on ML/AI in the world of fintech.)

]]> Analytics vs. Data Science vs. ML Research: Economist Sonali Syngal Shares Her View Sonali Syngal - Senior Scientist at Mastercard, Q McCallum - Senior Content Advisor at Formulatedby 00:51:30 The world of data has a lot of hazy definitions. This leads to confusion as people use the same terms in a conversation but mean very different things. Three such terms that are often conflated are "analytics," "data science," and "machine learning research." How do we tell the difference between them? And what are the different duties and qualifications of these roles? The world of data has a lot of hazy definitions. This leads to confusion as people use the same terms in a conversation but mean very different things. Three such terms that are often conflated are "analytics," "data science," and "machine learning research." How do we tell the difference between them? And what are the different duties and qualifications of these roles? machine learning research, data science salon, data scientist, analytics, data science, big data, economist, ai, machine learning false full 15 6f2b96c1-74d2-4f3a-a189-f5a24c6e934f Charting a Course: from Physics PhD to Professional Data Scientist with Dr Resham Sarkar What was it like to move from a physics lab into the data scientist's chair?  How did she find that first job? And what elements of her PhD experience have proven especially valuable in her machine learning work?  Join us in this conversation to find out.

  • Dr Sarkar works on machine learning at Slice . (She's hiring!)
  • You can also find her on LinkedIn.
]]> Tue, 13 Apr 2021 12:00:00 +0000 anna@formulatedby.com (Dr. Resham Sarkar - ML Expert & Head of Personalization at Slice, Q McCallum - Senior Content Advisor at Formulatedby) https://data-science-salon-podcast.simplecast.com/episodes/charting-a-course-from-physics-phd-to-professional-data-scientist-with-dr-resham-sarkar-rRvtlGuB What was it like to move from a physics lab into the data scientist's chair?  How did she find that first job? And what elements of her PhD experience have proven especially valuable in her machine learning work?  Join us in this conversation to find out.

  • Dr Sarkar works on machine learning at Slice . (She's hiring!)
  • You can also find her on LinkedIn.
]]> Charting a Course: from Physics PhD to Professional Data Scientist with Dr Resham Sarkar Dr. Resham Sarkar - ML Expert & Head of Personalization at Slice, Q McCallum - Senior Content Advisor at Formulatedby 00:47:16 There's no single path to a data scientist role. Practitioners come from fields as varied as software development, economics, and academia. Many people in that last group aren't sure what it's like to transition from an advanced degree program into industry. That's why I was happy to speak with Dr Resham Sarkar, a machine learning expert who heads up personalization at Slice. Before she started building ML around pizza, she completed a PhD in physics and then worked in insuretech. There's no single path to a data scientist role. Practitioners come from fields as varied as software development, economics, and academia. Many people in that last group aren't sure what it's like to transition from an advanced degree program into industry. That's why I was happy to speak with Dr Resham Sarkar, a machine learning expert who heads up personalization at Slice. Before she started building ML around pizza, she completed a PhD in physics and then worked in insuretech. ml, data scientist, data science, phd, big data, machine learning false full 14 568c6460-9f97-4637-8609-c7619f112146 Data Monetization Strategies with Micheline Casey Micheline has more than twenty years' experience at the intersection of data and money, and has been a Chief Data Officer (CDO) with 3 different organizations, leading and scaling data strategy, infrastructure, and platforms. She also led data commercialization efforts at Ford.  Her career includes early data brokers, automotive and logistics companies, financial services and insurance, health care, and energy.  Oh, and then there was that stint as the CDO of the Federal Reserve.  She's a real powerhouse in the data field and we're very happy that she was able to join us.

  • You can find Micheline on LinkedIn and Twitter
  • The paper Q mentioned early in this episode is Business Models for the Data Economy (McCallum, Gleason)
  • The book Micheline mentioned near the end is Doug Laney's Infonomics: How to Monetize, Manage, and Measure Information as an Asset for Competitive Advantage
]]> Thu, 25 Mar 2021 21:31:16 +0000 anna@formulatedby.com (Q McCallum - Senior Content Advisor at Formulatedby, Micheline Casey - Chief Data Officer) https://data-science-salon-podcast.simplecast.com/episodes/data-monetization-strategies-with-micheline-casey-3sPY4H43 Micheline has more than twenty years' experience at the intersection of data and money, and has been a Chief Data Officer (CDO) with 3 different organizations, leading and scaling data strategy, infrastructure, and platforms. She also led data commercialization efforts at Ford.  Her career includes early data brokers, automotive and logistics companies, financial services and insurance, health care, and energy.  Oh, and then there was that stint as the CDO of the Federal Reserve.  She's a real powerhouse in the data field and we're very happy that she was able to join us.

  • You can find Micheline on LinkedIn and Twitter
  • The paper Q mentioned early in this episode is Business Models for the Data Economy (McCallum, Gleason)
  • The book Micheline mentioned near the end is Doug Laney's Infonomics: How to Monetize, Manage, and Measure Information as an Asset for Competitive Advantage
]]> Data Monetization Strategies with Micheline Casey Q McCallum - Senior Content Advisor at Formulatedby, Micheline Casey - Chief Data Officer 00:49:49 The idea of turning data into money has been a draw since the early days of the term "Big Data." As many companies have learned, sometimes the hard way, this isn't always easy and it's hardly guaranteed to work. That's where today's guest comes in. For this episode, Formulatedby's Senior Content Advisor Q McCallum sat down with Micheline Casey to explore the what, why, and how of a company monetizing its data. There are a lot of matters to consider, ranging from technology to policy to business model, and she's seen them all. The idea of turning data into money has been a draw since the early days of the term "Big Data." As many companies have learned, sometimes the hard way, this isn't always easy and it's hardly guaranteed to work. That's where today's guest comes in. For this episode, Formulatedby's Senior Content Advisor Q McCallum sat down with Micheline Casey to explore the what, why, and how of a company monetizing its data. There are a lot of matters to consider, ranging from technology to policy to business model, and she's seen them all. fintech, monetizing data, ml, data science, big data false full 13 c8a9877e-6092-4bbd-8fc1-59b9849a91b4 Matt Godbolt: Software Testing, Performance Tuning, and Code Handoff for Data Scientists Data scientists and ML engineers write a lot of code: building data pipelines, wiring up models, and sometimes translating concepts from research papers into algorithms.  

Once in a while, that code runs into performance problems.  These can be painful to debug when you don't come from a formal software development background.  That's why Formulatedby's Senior Content Advisor Q McCallum rang up Matt Godbolt to learn the deep details of software testing, tracing performance bugs, working with data at scale, and how data scientists can work with developers to prepare their code for a production handoff.

Matt Godbolt has more than 30 years' experience writing code.  He's spent most of that time working in the performance-focused environments of console video games, high-frequency trading (HFT), and algorithmic trading.  Matt is the creator of the Compiler Explorer website, and also co-host of the Two's Complement podcast.

(Note from Q: My audio is a little choppy, but Matt's is perfect.  And you're here to hear him, anyway...)

 

Matt and Q mentioned a few links during their talk:

]]> Tue, 9 Mar 2021 01:38:22 +0000 anna@formulatedby.com (Matt Godbolt - Creator of the Compiler Explorer website, Q McCallum - Senior Content Advisor at Formulatedby) https://data-science-salon-podcast.simplecast.com/episodes/matt-godbolt-software-testing-performance-tuning-and-code-handoff-for-data-scientists-m3WNJMJZ Data scientists and ML engineers write a lot of code: building data pipelines, wiring up models, and sometimes translating concepts from research papers into algorithms.  

Once in a while, that code runs into performance problems.  These can be painful to debug when you don't come from a formal software development background.  That's why Formulatedby's Senior Content Advisor Q McCallum rang up Matt Godbolt to learn the deep details of software testing, tracing performance bugs, working with data at scale, and how data scientists can work with developers to prepare their code for a production handoff.

Matt Godbolt has more than 30 years' experience writing code.  He's spent most of that time working in the performance-focused environments of console video games, high-frequency trading (HFT), and algorithmic trading.  Matt is the creator of the Compiler Explorer website, and also co-host of the Two's Complement podcast.

(Note from Q: My audio is a little choppy, but Matt's is perfect.  And you're here to hear him, anyway...)

 

Matt and Q mentioned a few links during their talk:

]]> Matt Godbolt: Software Testing, Performance Tuning, and Code Handoff for Data Scientists Matt Godbolt - Creator of the Compiler Explorer website, Q McCallum - Senior Content Advisor at Formulatedby 01:08:14 Data scientists and ML engineers write a lot of code: building data pipelines, wiring up models, and sometimes translating concepts from research papers into algorithms. Data scientists and ML engineers write a lot of code: building data pipelines, wiring up models, and sometimes translating concepts from research papers into algorithms. code handoff, ml, data scientists, software testing, performance tuning, data science, machine learning false full 12 d4d9ca7a-b29e-4105-b98a-be9557874e6a Coffee Chat at DSSVirtual for Healthcare, Finance & Technology Fri, 19 Feb 2021 05:00:00 +0000 anna@formulatedby.com (Data Science Salon now AI Loves Data) https://data-science-salon-podcast.simplecast.com/episodes/coffee-chat-at-dssvirtual-for-healthcare-finance-technology-mYSWZ6lY Coffee Chat at DSSVirtual for Healthcare, Finance & Technology Data Science Salon now AI Loves Data 00:57:26 We recorded this episode at our February 2021 Data Science Salon Virtual on Healthcare, Finance & Technology. Formulated.by’s Senior Content Advisor, Q McCallum, sat down with Ayda Farhadi, Senior Data Scientist at UPS, and Vasileios Stathias, Lead Data Scientist at Sylvester Comprehensive Cancer Center to discuss applying AI to healthcare. We recorded this episode at our February 2021 Data Science Salon Virtual on Healthcare, Finance & Technology. Formulated.by’s Senior Content Advisor, Q McCallum, sat down with Ayda Farhadi, Senior Data Scientist at UPS, and Vasileios Stathias, Lead Data Scientist at Sylvester Comprehensive Cancer Center to discuss applying AI to healthcare. false full 11 672b3219-7667-4b80-b60d-224d7e312392 Trading, Risk, and Reinsurance with Otakar Hubschmann Our Senior Content Advisor Q McCallum sat down with Otakar Hubschmann, Head of Applied Data at TransRe, to talk about ML/AI in the world of reinsurance.  They take a deep dive into the insurance industry and the role reinsurance plays there, with a side-trip to show how this differs from the quantitative finance you see in hedge funds.  Along the way, Otakar offers his favorite tips for hiring data scientists.  (Whether you're applying for a job, or hiring for one, take note.) Near the end of the episode, Otakar and Q mention some of their favorite books on risk, machine learning, and taking a quantitative approach to businesses.  Here's the list they promised:

  • Against the Gods: The Remarkable Story of Risk (Bernstein)
  • Acts of God and Man: Ruminations on Risk and Insurance (Powers)
  • When Genius Failed (Lowenstein)
  • The Smartest Guys in the Room (McLean)
  • Moneyball (Lewis)
  • The Big Short (Lewis)
  • Models Behaving Badly (Derman)
  • The Gray Rhino (Wucker)
  • Bad Blood: Secrets and Lies in a Silicon Valley Startup (Carreyrou)
  • The Quants (Scott Patterson)
  • A Man for All Markets (Edward Thorp)
  • Fortune's Formula (Poundstone)
  • The Man Who Solved the Markets (Zuckerman)
  • Artificial Intelligence (Norvig)
  • Deep Learning (Goodfellow)
  • Python Machine Learning (Raschka)
  • Python for Data Analysis (McKinney)
  • An Introduction to Statistical Learning: with Applications in R (James, Wittin, Hastie, Tibshirani)
  • The Visual Display of Quantitative Information (Tufte)

Also, to learn more about the insurance industry, please check out David Wright's Not Unreasonable podcast.  Otakar's interview on that show is the episode from November 02, 2020.

]]> Tue, 2 Feb 2021 14:30:00 +0000 anna@formulatedby.com (Otakar Hubschmann - Head of Applied Data at TransRe, Q McCallum - Senior Content Advisor at Formulatedby) https://data-science-salon-podcast.simplecast.com/episodes/trading-risk-and-reinsurance-with-otakar-hubschmann-3I255zKm Our Senior Content Advisor Q McCallum sat down with Otakar Hubschmann, Head of Applied Data at TransRe, to talk about ML/AI in the world of reinsurance.  They take a deep dive into the insurance industry and the role reinsurance plays there, with a side-trip to show how this differs from the quantitative finance you see in hedge funds.  Along the way, Otakar offers his favorite tips for hiring data scientists.  (Whether you're applying for a job, or hiring for one, take note.) Near the end of the episode, Otakar and Q mention some of their favorite books on risk, machine learning, and taking a quantitative approach to businesses.  Here's the list they promised:

  • Against the Gods: The Remarkable Story of Risk (Bernstein)
  • Acts of God and Man: Ruminations on Risk and Insurance (Powers)
  • When Genius Failed (Lowenstein)
  • The Smartest Guys in the Room (McLean)
  • Moneyball (Lewis)
  • The Big Short (Lewis)
  • Models Behaving Badly (Derman)
  • The Gray Rhino (Wucker)
  • Bad Blood: Secrets and Lies in a Silicon Valley Startup (Carreyrou)
  • The Quants (Scott Patterson)
  • A Man for All Markets (Edward Thorp)
  • Fortune's Formula (Poundstone)
  • The Man Who Solved the Markets (Zuckerman)
  • Artificial Intelligence (Norvig)
  • Deep Learning (Goodfellow)
  • Python Machine Learning (Raschka)
  • Python for Data Analysis (McKinney)
  • An Introduction to Statistical Learning: with Applications in R (James, Wittin, Hastie, Tibshirani)
  • The Visual Display of Quantitative Information (Tufte)

Also, to learn more about the insurance industry, please check out David Wright's Not Unreasonable podcast.  Otakar's interview on that show is the episode from November 02, 2020.

]]> Trading, Risk, and Reinsurance with Otakar Hubschmann Otakar Hubschmann - Head of Applied Data at TransRe, Q McCallum - Senior Content Advisor at Formulatedby 00:58:34 Our Senior Content Advisor Q McCallum sat down with Otakar Hubschmann, Head of Applied Data at TransRe, to talk about ML/AI in the world of reinsurance.  They take a deep dive into the insurance industry and the role reinsurance plays there, with a side-trip to show how this differs from the quantitative finance you see in hedge funds. Our Senior Content Advisor Q McCallum sat down with Otakar Hubschmann, Head of Applied Data at TransRe, to talk about ML/AI in the world of reinsurance.  They take a deep dive into the insurance industry and the role reinsurance plays there, with a side-trip to show how this differs from the quantitative finance you see in hedge funds. ml, finance, insurance, artificial intelligence, ai, machine learning false full 10 27f70b72-92fb-42ce-9265-5c5092ba88d1 Coffee Chat at DSSVirtual for Finance & Technology Mon, 14 Dec 2020 16:30:22 +0000 anna@formulatedby.com (Sonali Syngal – Applied Scientist and Project Lead AI Garage at Mastercard, Jeff Sharpe – Senior Manager / Tech Lead at CapitalOne, Thulasi Nambiar – Senior Manager of Marketing Data Science at Prosper) https://data-science-salon-podcast.simplecast.com/episodes/coffee-chat-at-dssvirtual-for-finance-technology-WIm9ULcA Coffee Chat at DSSVirtual for Finance & Technology Sonali Syngal – Applied Scientist and Project Lead AI Garage at Mastercard, Jeff Sharpe – Senior Manager / Tech Lead at CapitalOne, Thulasi Nambiar – Senior Manager of Marketing Data Science at Prosper 00:56:37 We recorded this episode at our December 2020 Data Science Salon Virtual on Finance & Technology. Formulated.by’s Senior Content Advisor, Q McCallum, sat down with some new friends to discuss trends and challenges in the world of AI. We recorded this episode at our December 2020 Data Science Salon Virtual on Finance & Technology. Formulated.by’s Senior Content Advisor, Q McCallum, sat down with some new friends to discuss trends and challenges in the world of AI. ml, data science, artificial intelligence, ai, machine learning false full 9 3716d40b-268b-451c-ad1a-af6cf3a6e7b8 Coffee Chat from DSS Virtual - Retail & E-Commerce Phillip Rossi, Head of Data Science at Shopify, Laya Shamgah, Data Scientist at Lowe's Company, Jeffrey Yau, Head of Data Science at Walmart Labs, Samantha Cvetkovski, Data Science Manager at Mindbody

]]> Fri, 20 Nov 2020 19:13:58 +0000 anna@formulatedby.com (Phillip Rossi - Head of Data Science at Shopify, Jeffrey Yau - Head of Data Science at Walmart Labs, Laya Shamgah - Data Scientist at Lowe's Company, Samantha Cvetkovski - Data Science Manager at Mindbody) https://data-science-salon-podcast.simplecast.com/episodes/coffee-chat-from-dss-virtual-retail-e-commerce-AVZ1wy__ Phillip Rossi, Head of Data Science at Shopify, Laya Shamgah, Data Scientist at Lowe's Company, Jeffrey Yau, Head of Data Science at Walmart Labs, Samantha Cvetkovski, Data Science Manager at Mindbody

]]> Coffee Chat from DSS Virtual - Retail & E-Commerce Phillip Rossi - Head of Data Science at Shopify, Jeffrey Yau - Head of Data Science at Walmart Labs, Laya Shamgah - Data Scientist at Lowe's Company, Samantha Cvetkovski - Data Science Manager at Mindbody 00:52:42 We recorded this episode at our November 2020 Virtual Data Science Salon on Retail & Ecommerce. Formulated.by’s Content Advisor, Roger Magoulas, sat down with some of the event's speakers to talk about data science trends and challenges in retail & ecommerce. We recorded this episode at our November 2020 Virtual Data Science Salon on Retail & Ecommerce. Formulated.by’s Content Advisor, Roger Magoulas, sat down with some of the event's speakers to talk about data science trends and challenges in retail & ecommerce. artificial intelligence, e-commerce, retail, ai, machine learning false full 8 177ea15a-4b42-47fe-a7fb-a60b4c2edc66 Shane Glynn on Automated Content Moderation and the Intersection of AI and Law Today's podcast is about the intersection of AI and the law.  Formulatedby's Senior Content Advisor, Q McCallum, spoke with Shane Glynn, an attorney who has deep knowledge of the tech and AI worlds.  He's worked for a couple of law firms that you may have heard of, and for a tech company that you have most certainly heard of.Shane gave us an attorney's view on AI practices, explored the ways in which an attorney can help with an AI effort, and explained the how, when, and why AI teams should involve their legal counsel.  (Hint: early. Very early.) Shane also talked about the legal and technical aspects of AI-driven, automated content moderation.At the end of the episode, Shane mentions some blog posts that Q wrote on AI lessons learned from the world of algorithmic trading.  That series starts here.

]]> Mon, 9 Nov 2020 15:00:00 +0000 anna@formulatedby.com (Q McCallum - Senior Content Advisor at Formulatedby, Shane Glynn - Attorney) https://data-science-salon-podcast.simplecast.com/episodes/shane-glynn-on-automated-content-moderation-and-the-intersection-of-ai-and-law-dmPFslPO Today's podcast is about the intersection of AI and the law.  Formulatedby's Senior Content Advisor, Q McCallum, spoke with Shane Glynn, an attorney who has deep knowledge of the tech and AI worlds.  He's worked for a couple of law firms that you may have heard of, and for a tech company that you have most certainly heard of.Shane gave us an attorney's view on AI practices, explored the ways in which an attorney can help with an AI effort, and explained the how, when, and why AI teams should involve their legal counsel.  (Hint: early. Very early.) Shane also talked about the legal and technical aspects of AI-driven, automated content moderation.At the end of the episode, Shane mentions some blog posts that Q wrote on AI lessons learned from the world of algorithmic trading.  That series starts here.

]]> Shane Glynn on Automated Content Moderation and the Intersection of AI and Law Q McCallum - Senior Content Advisor at Formulatedby, Shane Glynn - Attorney 01:02:15 Today's podcast is about the intersection of AI and the law. Formulatedby's Senior Content Advisor, Q McCallum, spoke with Shane Glynn, an attorney who has deep knowledge of the tech and AI worlds. Today's podcast is about the intersection of AI and the law. Formulatedby's Senior Content Advisor, Q McCallum, spoke with Shane Glynn, an attorney who has deep knowledge of the tech and AI worlds. tech, legal, technology, data science, ai false full 7 68d7edc2-aba8-417c-aa94-2145ae9760aa Coffee Chat from DSS Virtual - Media, Advertising, & Entertainment Wed, 30 Sep 2020 17:34:47 +0000 anna@formulatedby.com (Anne Bauer - Director of Data Science at The New York Times, Q McCallum - Senior Content Advisor at Formulatedby, Kim Martin - Data Science Manager at Netflix, Yves Bergquist - Program Director of AI & Neuroscience in Media Entertainment Technology Center at USC, Dominick Rocco - Data Scientist at PhData) https://data-science-salon-podcast.simplecast.com/episodes/coffee-chat-from-dss-virtual-media-advertising-entertainment-zu_UdecZ Coffee Chat from DSS Virtual - Media, Advertising, & Entertainment Anne Bauer - Director of Data Science at The New York Times, Q McCallum - Senior Content Advisor at Formulatedby, Kim Martin - Data Science Manager at Netflix, Yves Bergquist - Program Director of AI & Neuroscience in Media Entertainment Technology Center at USC, Dominick Rocco - Data Scientist at PhData 00:53:18 We recorded this episode at our September 2020 Data Science Salon virtual event on Media, Advertising, & Entertainment. Formulatedby's Senior Content Advisor, Q McCallum, sat down with some new friends to discuss trends and challenges in the world of AI: Anne Bauer | Director of Data Science at The New York Times Yves Bergquist | Director of the AI & Neuroscience in Media Project, at USC Kim Martin | Engineering Leader of Data Science and Engineering at Netflix Dominick Rocco | Data Scientist at phData We recorded this episode at our September 2020 Data Science Salon virtual event on Media, Advertising, & Entertainment. Formulatedby's Senior Content Advisor, Q McCallum, sat down with some new friends to discuss trends and challenges in the world of AI: Anne Bauer | Director of Data Science at The New York Times Yves Bergquist | Director of the AI & Neuroscience in Media Project, at USC Kim Martin | Engineering Leader of Data Science and Engineering at Netflix Dominick Rocco | Data Scientist at phData false full 6 c5b26467-c6df-417c-809a-7f1cf0f7532f Mission and Purpose in Data Science: Lessons from the Military and Intelligence Richard Dunks served as a member of the US Army and the intelligence community (IC), where he honed skills that he now uses in his civilian pursuits as a data scientist, trainer, and educator.   He recently caught up with Q McCallum (Senior Content Advisor at Formulatedby, the company behind Data Science Salon) to talk about what his time in the IC taught him about data analysis, having a sense of mission, and what it means to lose trust in data.

]]> Wed, 16 Sep 2020 12:30:09 +0000 anna@formulatedby.com (Richard Dunks - founder of Datapolitan, Q McCallum - Senior Content Advisor at Formulatedby) https://data-science-salon-podcast.simplecast.com/episodes/mission-and-purpose-in-data-science-lessons-from-the-military-and-intelligence-OojY3OmE Richard Dunks served as a member of the US Army and the intelligence community (IC), where he honed skills that he now uses in his civilian pursuits as a data scientist, trainer, and educator.   He recently caught up with Q McCallum (Senior Content Advisor at Formulatedby, the company behind Data Science Salon) to talk about what his time in the IC taught him about data analysis, having a sense of mission, and what it means to lose trust in data.

]]> Mission and Purpose in Data Science: Lessons from the Military and Intelligence Richard Dunks - founder of Datapolitan, Q McCallum - Senior Content Advisor at Formulatedby 00:48:34 How can mission and purpose drive a data professional? And what happens when we can no longer trust the data that's presented to us? How can mission and purpose drive a data professional? And what happens when we can no longer trust the data that's presented to us? false full 5 1920d078-fc22-4a75-a41d-5c643d863c6f Marcello La Rocca on Algorithms and Data Structures Q McCallum (Senior Content Advisor at Formulatedby, the company behind Data Science Salon) met up with Marcello La Rocca, someone who compiled his extensive knowledge of algorithms into a rather hefty book on the topic.  In this episode, the author of Algorithms and Data Structures in Action talks about the study of algorithms, why they're useful, and how he's applied them to oversized datasets.  Marcello closes out with his thoughts on (sometimes, not) using algorithms in tech job interviews.

]]> Wed, 2 Sep 2020 12:00:16 +0000 anna@formulatedby.com (Q McCallum - Senior Content Advisor at Formulatedby, Marcello La Rocca - Author of Algorithms and Data Structures in Action) https://data-science-salon-podcast.simplecast.com/episodes/marcello-la-rocca-on-algorithms-and-data-structures-IQ_n0zhl Q McCallum (Senior Content Advisor at Formulatedby, the company behind Data Science Salon) met up with Marcello La Rocca, someone who compiled his extensive knowledge of algorithms into a rather hefty book on the topic.  In this episode, the author of Algorithms and Data Structures in Action talks about the study of algorithms, why they're useful, and how he's applied them to oversized datasets.  Marcello closes out with his thoughts on (sometimes, not) using algorithms in tech job interviews.

]]> Marcello La Rocca on Algorithms and Data Structures Q McCallum - Senior Content Advisor at Formulatedby, Marcello La Rocca - Author of Algorithms and Data Structures in Action 01:02:54 The term "algorithms" has several meanings, from machine learning models to tools of Wall St traders. Then there's the classic computer science definition: a set of instructions for solving problems. Think "simulated annealing," "evolutionary computing," or "LRU cache." These are the sort of algorithms we'll explore today. The term "algorithms" has several meanings, from machine learning models to tools of Wall St traders. Then there's the classic computer science definition: a set of instructions for solving problems. Think "simulated annealing," "evolutionary computing," or "LRU cache." These are the sort of algorithms we'll explore today. ml, algorithms, data structures, data science, machine learning false full 4 40e99c8b-ad7c-4330-b77f-11fc4aca9083 Jean-Georges Perrin on Spark and Data Quality Wed, 5 Aug 2020 12:20:11 +0000 anna@formulatedby.com (Q McAllum - Senior Content Advisor at Formulatedby, Jean-Georges Perrin - Author of Spark in Action 2nd Edition) https://data-science-salon-podcast.simplecast.com/episodes/spark-in-action-b5Rd5e4F Jean-Georges Perrin on Spark and Data Quality Q McAllum - Senior Content Advisor at Formulatedby, Jean-Georges Perrin - Author of Spark in Action 2nd Edition 01:03:54 Our guest for this episode is Jean-Georges Perrin, the author of Spark in Action, 2nd edition. We talk about his career path (he's been doing "big data" since before the term existed), what inspired him to write Spark in Action, and where Spark fits in your company's data efforts. He also shares his thoughts on data quality. Our guest for this episode is Jean-Georges Perrin, the author of Spark in Action, 2nd edition. We talk about his career path (he's been doing "big data" since before the term existed), what inspired him to write Spark in Action, and where Spark fits in your company's data efforts. He also shares his thoughts on data quality. ml, spark, tech, technology, data scientist, data science, ai false full 3 9d53d91b-6ec8-4e92-a2ce-ea5444f76d5a Applications of Data Science in Media & Entertainment Mon, 21 Oct 2019 15:06:26 +0000 anna@formulatedby.com (Ayan Battacharya - Advanced Analytics Specialist Leader at Deloitte Consulting, Harini Krishnan - Data Scientist at Capsule8) https://data-science-salon-podcast.simplecast.com/episodes/application-of-data-science-in-media-entertainment-EvLx3LDG Applications of Data Science in Media & Entertainment Ayan Battacharya - Advanced Analytics Specialist Leader at Deloitte Consulting, Harini Krishnan - Data Scientist at Capsule8 00:41:59 The Media and Entertainment industry has undeniably been heavily disrupted by changes in technology. Listen as Ayan Battacharya, Advanced Analytics Specialist Leader at Deloitte Consulting and Harini Krishnan, Data Scientist at Capsule8, share observations they've garnered from their own experience on the state of data science in Media & Entertainment, live from DSS NYC 2019. The Media and Entertainment industry has undeniably been heavily disrupted by changes in technology. Listen as Ayan Battacharya, Advanced Analytics Specialist Leader at Deloitte Consulting and Harini Krishnan, Data Scientist at Capsule8, share observations they've garnered from their own experience on the state of data science in Media & Entertainment, live from DSS NYC 2019. data scientist, tech, media, data science, entertainment, ml, ai, technology false full 2 7bd3fbab-124f-4b4b-8ee8-f5d7b2bd1156 Prolific vs. private data in media advertising @ DSS NYC Fri, 12 Jul 2019 13:50:50 +0000 anna@formulatedby.com (Formulatedby, Sergey Fogelson, Lauren Lombardo, Q McCallum) https://data-science-salon-podcast.simplecast.com/episodes/untitled-H6W0UP0l Prolific vs. private data in media advertising @ DSS NYC Formulatedby, Sergey Fogelson, Lauren Lombardo, Q McCallum 01:03:50 In June 2019, over 200 data scientists gathered at Viacom HQ in New York to hear key industry players’ takes on what makes an effective data-driven strategy. Q McCallum, Senior Content Adviser at Formulated.by, took a deeper dive into the major topics of concern for data science when he spoke with DSS NYC speakers Lauren Lombardo, Senior Data Scientist at Nielsen and Sergey Fogelson, Vice President of Data Science and Modeling at Viacom. Listen as they speak about current practices and debate the ways in which the growth of AI will impact advertising In June 2019, over 200 data scientists gathered at Viacom HQ in New York to hear key industry players’ takes on what makes an effective data-driven strategy. Q McCallum, Senior Content Adviser at Formulated.by, took a deeper dive into the major topics of concern for data science when he spoke with DSS NYC speakers Lauren Lombardo, Senior Data Scientist at Nielsen and Sergey Fogelson, Vice President of Data Science and Modeling at Viacom. Listen as they speak about current practices and debate the ways in which the growth of AI will impact advertising false full 1