All Episodes
Data Science Leaders — 100 episodes
The Cave: Pharma's Data Problem
Turning Governance Into the “Yes” Guys
Building Trust for Transformation in Enterprise AI
Engineering the Future of Health with AI and Data
The Rise of the Self-Driving Organization
The Cultural Shifts That Power AI Adoption
The AI Race: Predictions for AI in National Security & the Public Sector
The Future of Enterprise AI? AI in Production!
The Silent Future of AI in Financial Services
Pharma Is the New Tech: The Future of AI in Life Sciences
AI Predictions for 2025: The Boogeyman, Agentic AI & Governance
Realizing AI Value Through Governance in Insurance
Mastering AI Governance with Forrester & the Federal Reserve
Crossover: Ethical Machines and AI Governance
AI Transformation in Government: Lessons from Unit X
The EU AI Act: Key Strategies for Regulatory Compliance
AI Governance in Action: Lessons from the Trenches
Demystifying the Top 5 Questions of AI Governance
Operationalizing privacy in the age of AI
Optimizing Your Architecture for AI Innovation: BARC Survey Results
Driving Digital Strategy with AI at OneAmerica
AI-driven Marketing, Optimization, Consciousness and CAIOs
Trust and faster AI time to value in manufacturing at IFF
How to Make Responsible AI Happen: A Historical View
Efficient Data Pipelines for AI and a Healthier World
Enabling AI on Enormous Financial Datasets at FINRA
Developing a Strategy for AI Transformation at Zendesk
Surviving and Thriving as an AI Leader in a GenAI World
Unlocking the Disruptive Potential of Generative AI: A VC Perspective
Overcoming the Data Challenges of AI-driven Drug Discovery
AI Will Plan Your Next Vacation: GenAI at Tripadvisor
From the Archive: A Hybrid Approach to Accelerating the Model Lifecycle
Unlocking AI in the Public Sector
Disrupting Drug Discovery and Development With AI
Mastering the Rare Art of ML Deployment
Shattering the Myths of GenAI: Interview with Forrester Analyst Rowan Curran
More Human Than Human? GenAI Customer Service at Bolt
AI in 2024: Predictions on the Future of the AI Revolution
The State and Future of Generative AI: Reflections on the Anniversary of ChatGPT with Anaconda CEO Peter Wang
CDOs: Changing the Operating Model for Data & AI Transformation
Transforming Education with Generative AI and Active Learning
“Lessons from the First GenAI Killer App"
Honeywell: Delivering on the Power of Outlier Detection
Making Better Sustainability Decisions with AI
Celebrity Guest Gregory Zuckerman: Trusting AI to Make the Decisions
Solving the AI Talent Gap: Upskilling at Scale at Halliburton
The AI Innovator’s Dilemma: Insights from Harvard’s D^3 Institute
Get the Most Out of Generative AI
Celebrity Guest Reid Blackman: Who’s Responsible for Responsible AI?
Output to Outcomes: AI Product Management at Verizon
Celebrity Guest Steven Levy: AI, a mirror to human intelligence
Season 2: Host to Host
What It Takes to Productize Next-Gen AI on a Global Scale (Srujana Kaddevarmuth, Senior Director of Data & Machine Learning Programs, Walmar
Help Me Help You: Forging Productive Partnerships with Business Stakeholders (Sunil Kumar Vuppala, Director of Global Artificial Intelligenc
Change Management Strategies for Data & Analytics Transformations (Michal Levitzky Head of Data & Analytics - CDO, Migdal Group)
A Hybrid Approach to Accelerating the Model Lifecycle (David Von Dollen, Head of AI, Volkswagen of America)
Giving Back and Building Your Brand as a Data Science Leader (Sidney Madison Prescott, Global Head of Intelligent Automation - RPA, AI, ML,
Governing Models and Structuring Teams in Highly Regulated Industries (Anju Gupta, VP Data Science & Analytics, Northwestern Mutual)
How to Operationalize, Scale, and Measure AI in Life Sciences (Sidd Bhattacharya, Director of Healthcare Analytics & AI, PwC)
Getting to Ground Truth with Strategies from ML in Electronics Manufacturing (Alon Malki, Senior Director of Data Science, NI)
Elevating Your Team as Strategic Business Partners (Indy Mondal, Senior Director of Data Science, AI & Product Insights, DocuSign)
A Journey Through the Data Science & Analytics Value Chain (Nancy Hersh, Chief Data Officer, Arcadia)
Decoding Human Behavior and Well-Being through Data Science (Takuya Kitagawa, Chief Data Officer & Managing Executive Officer, Rakuten Group
Motivating Teams and Combating Bias in Healthcare Data Science (Vikram Bandugula, Senior Director of Data Science, Anthem)
Data in the DNA: Breaking Down the Autonomous Enterprise (Janet George, Enterprise AI Leader & Author)
Embedding Responsible AI in Your Models and Your Team (Anand Rao, Global Artificial Intelligence Lead, PwC)
Supply Chain Solutions & the Role of the ML Engineer (Karin Chu, VP Data Science & Digital Analytics, Peapod Digital Labs)
Legal Analytics: Winning Business, Winning Cases, and Winning Over Your General Counsel (Peter Geovanes, Head of Data Strategy, AI & Analyti
Empowering Big Teams to Take on Even Bigger ML Challenges (Jan Neumann, Executive Director, Machine Learning, Comcast)
Change Management: Winning Over AI Skeptics in Banking & Beyond (Chun Schiros, SVP, Head of Enterprise Data Science Group, Regions Bank)
To Patent or Not to Patent? How to Weigh the Options for Your Team (Kli Pappas, Associate Director of Global Analytics, Colgate-Palmolive)
How a Centralized Data Science “Nerve Center” Can Power Global Impact (Tim Suhling, VP Global Business Intelligence, Ingram Micro)
Scaling Data Science Value with Cross-Functional Teams (Jayesh Govindarajan, SVP Data Science & Engineering, Salesforce)
Modernizing Healthcare Through Data Science and Digital Transformation (Kaushik Raha, VP Data Science & Health Content Operations, Elsevier)
How Data Science Teams Are Going Deeper with Proof of Value (Nimit Jain, Head of Data Science, Novartis)
Why It Pays to Stand Out From the Crowd in Data Science (Bob Bress, Head of Data Science, FreeWheel)
Tracking Business Value with Data Science Portfolio Management (Katya Hall, Director of Enterprise Analytics, McKesson)
How to Launch a Data Science Team Built for Scale (Mike Foley, Senior Director of Data Science, Hitachi Vantara)
Exploring the Future of Data: Regulations & Managing Analytics Teams (John Thompson, Global Head of Advanced Analytics & AI, CSL Behring)
Data Challenges and the Promising Role of Product Analytics in Healthcare
People Analytics: Data Science, Ethics, and Opportunity in HR (Adam McElhinney, Chief Data Science Officer, VP of Data Insights, Paylocity)
Lessons from Building a 2,700-Person Analytics Team (Dave Frankenfield, VP Enterprise Data & Analytics, Optum)
Oncology Analytics & Delivering Insights from Messy Data (Susan Hoang, VP Oncology Analytics, McKesson)
How Computer Science & Statistics Fundamentals Can Advance Data Science in 2021 (Chris Volinsky, AVP Data Science & AI Research, AT&T)
Getting Started with Deep Learning in the Enterprise (Eitan Anzenberg, Chief Data Scientist, Bill.com)
Communication in Data Science: Know the Data & Know the Business (Gaia Bellone, SVP - Head of Data Science at KeyBank)
The Right and Wrong Place for the Citizen Data Scientist (Romain Ramora, Head of Data Science & Innovation - Supply Chain at Cisco)
What Happens When You Bring Data Science and Data Engineering Under One Roof (Mark Teflian, VP, Data Science & Data Engineering, Charter Com
How to Answer the #1 Question in Enterprise Data Science: “So What?” (Khatereh Khodavirdi, Global Head of Analytics & Data Science - Global
The Past, Present, and Fascinating Future of Data Science (Mike Tamir, Chief ML Scientist and Head of Machine Learning/AI, SIG)
Industry 4.0: Data Science in Manufacturing (Paul Turner, VP Industry 4.0 Applications & Analytics, Stanley Black & Decker)
The 3 Biggest Jobs of Any Chief Data Officer (Heidi Lanford, Chief Data Officer, Fitch Group)
Navigating Data Constraints in the Highly-Regulated Healthcare Industry (Derrick Higgins, Head of Enterprise Data Science & AI, Blue Cross a
Bioinformatics and the Unprecedented COVID-19 Vaccine Race (Fiona Hyland, Director of R&D, Informatics, Thermo Fisher Scientific)
Bridging the Gap Between Data Science and Business Outcomes
Challenges and Opportunities in Operationalizing Data Science
How to Be a Truth-Seeking, Truth-Telling Partner in Data Science
How to Use AI Reliability to Identify and Predict Model Decay
More than Models: Building a Culture of Data Literacy and Data Ethics
An Introduction to Data Science Leaders, a Podcast for Daring Data Science Teams