High Signal: Data Science | Career | AI

Episode 13: The End of Programming As We Know It

March 27th, 2025  |  1 hr 23 mins

ai, data science, genai, llms, machine learning

Tim O’Reilly—founder of O’Reilly Media and one of the most influential voices in tech—argues we’re not witnessing the end of programming, but the beginning of something far bigger. He draws on past computing revolutions to explore how AI is reshaping what it means to build software, why real breakthroughs come from the edge—not incumbents—and what it takes to learn, teach, and build responsibly in the age of AI.

Episode 12: Your Machine Learning Solves The Wrong Problem

March 13th, 2025  |  54 mins 40 secs

causal inference, causal ml, data science, machine learning

Stefan Wager—Professor at Stanford and expert on causal machine learning—has worked with leading tech companies including Dropbox, Facebook, Google, and Uber. He challenges the widespread assumption that better predictions mean better decisions. Traditional machine learning excels at prediction, but is prediction really what your business needs? Stefan explores why predictive models alone often fail to answer critical “what-if” questions, how causal machine learning bridges this gap, and provides practical advice for how you can start applying causal ML at work.

Episode 11: What Comes After Code? The Role of Engineers in an AI-Driven Future

February 27th, 2025  |  1 hr 5 mins

Peter Wang—Chief AI Officer at Anaconda and a driving force behind PyData—challenges conventional thinking about AI’s role in software development. As AI reshapes engineering, are we moving beyond writing code to orchestrating intelligence? Peter explores why companies are fixated on models instead of integration, how AI is breaking traditional software workflows, and what this shift means for open source. He also shares insights on the evolving role of engineers, the commoditization of AI models, and the deeper questions we should be asking about the future of software.

Episode 10: AI Won't Save You But Data Intelligence Will

February 12th, 2025  |  59 mins 42 secs

ai, data science, machine learning

Ari Kaplan—Global Head of Evangelism at Databricks and a pioneer in sports analytics—explains why businesses fixated on AI often overlook the real advantage: making better decisions with their own data. He shares lessons from his work building analytics teams for Major League Baseball, advising McLaren’s F1 strategy, and helping companies apply AI where it actually works—without falling into hype-driven traps.

Episode 9: Why 90% of Data Science Fails—And How to Fix It -- With Eric Colson

January 30th, 2025  |  1 hr 9 mins

ai, data science, machine learning

Eric Colson—former Chief Algorithms Officer at Stitch Fix and VP of Data Science and Machine Learning at Netflix—explains why most companies fail to fully leverage their data science teams. Drawing on his experience leading data functions at top tech companies, he shares how organizations can move beyond treating data science as a support function and instead empower data scientists to drive strategic impact through experimentation, iteration, and algorithmic decision-making.

Episode 8: From Zero to Scale: Lessons from Airbnb and Beyond

January 9th, 2025  |  1 hr 6 mins

ai, data science, machine learning

Elena Grewal—former Head of Data Science at Airbnb, political consultant, professor at Yale, and ice cream shop owner—shares her journey of building data teams that scale across vastly different contexts. Drawing on her experiences in tech, consulting, and brick-and-mortar, Elena offers practical lessons on leadership, trust, and experimentation.

Episode 7: What Lies Beyond Machine Learning and AI: Decision Systems and the Future of Data Teams

December 18th, 2024  |  1 hr 18 mins

ai, data science, genai, llms, machine learning

In this episode of High Signal, Chris Wiggins—Chief Data Scientist at The New York Times, Professor at Columbia University, and co-author of How Data Happened—shares how organizations can move beyond prediction to actionable decision systems. Drawing on his work at The New York Times and in academia, Chris explains how to scale data teams, optimize systems, and align data science with organizational impact.

Episode 6: What Happens to Data Science in the Age of AI?

December 4th, 2024  |  1 hr 18 mins

data science, genai, llms, machine learning, nlp, prompt engineering

In this episode of High Signal, Hilary Mason—renowned data scientist, entrepreneur, and co-founder of Hidden Door—shares her unique insights into the evolving world of data science and generative AI. Drawing from her pioneering work at Fast Forward Labs, Bitly, and Hidden Door, Hilary explores how creativity, judgment, and empathy are reshaping the data landscape.

Episode 5: The Hard Truth About Building AI Systems and What Most Leaders Miss About AI

November 20th, 2024  |  1 hr 2 mins

ai, data science, machine learning

In this episode of High Signal, Gabriel Weintraub (the Amman Professor of Operations, Information, and Technology at Stanford Graduate School of Business), brings his expertise in market design, data science, and operations, enriched by his experience with global platforms like Uber and Mercado Libre, to a conversation that spans practical strategies, cultural insights, and global perspectives on data and AI.

Episode 4: How to Build an Experimentation Machine and Where Most Go Wrong

November 7th, 2024  |  51 mins 16 secs

Ramesh Johari (Stanford, Uber, Airbnb, and more) explores the art and science of online experimentation, especially in the context of marketplaces and tech companies.

Episode 3: Data Science Meets Management: Teamwork, Experimentation, and Decision-Making

October 19th, 2024  |  52 mins 12 secs

Chiara Farronato (Harvard Business School) discusses how digital platforms like Airbnb and Uber have transformed industries. She explores the challenges of fostering collaboration between managers and data scientists, bridging communication gaps, and building data-driven cultures. Chiara also delves into the complexities of managing peer-to-peer marketplaces and the evolving role of data in decision-making. This episode offers key insights for business leaders working with technical teams and navigating platform-based innovation.

Episode 2: Fooling Yourself Less: The Art of Statistical Thinking in AI

October 19th, 2024  |  1 hr 51 secs

Hugo Bowne-Anderson welcomes Andrew Gelman, professor at Columbia University, to discuss the practical side of statistics and data science. They explore the importance of high-quality data, computational skills, and using simulation to avoid misleading results. Andrew dives into real-world applications like election predictions and highlights causal inference’s critical role in decision-making. This episode offers insights into balancing statistical theory with applied data analysis, making it a must-listen for both data practitioners and those interested in how statistics shapes our world.

Episode 1: The Next Evolution of AI: Markets, Uncertainty, and Engineering Intelligence at Scale

October 19th, 2024  |  1 hr 15 mins

Michael Jordan (UC Berkeley) on the future of machine learning as it extends to a planetary scale in "The Next Evolution of AI: Markets, Uncertainty, and Engineering Intelligence at Scale." In this episode, Mike speaks with Hugo about the evolution of AI, the importance of integrating machine learning, computer science, and economics, and how AI can scale to address planetary-level challenges.