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PODCAST

High Signal: Data Science | Career | AI

Welcome to High Signal, the podcast for data science, AI, and machine learning professionals. High Signal brings you the best from the best in data science, machine learning, and AI. Hosted by Hugo Bowne-Anderson and produced by Delphina, each episode features deep conversations with leading experts, such as Michael Jordan (UC Berkeley), Andrew Gelman (Columbia) and Chiara Farranato (HBS). Join us for practical insights from the best to help you advance your career and make an impact in these

technology

All Episodes

1:09:40

Episode 9: Why 90% of Data Science Fails—And How to...

High Signal: Data Science | Career | AI ·

2025/01/30

In this episode of High Signal, Eric Colson—former Chief Algorithms Officer at Stitch Fix and VP of Data Science and Machine Learning at Netflix—breaks down why most companies fail to unlock the full potential of their data science teams. Drawing from years of experience leading data functions at top tech companies, Eric shares how organizations can shift from treating data scientists as a service function to empowering them as strategic drivers of business impact. Key topics from the conversation

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1:06:42

Episode 8: From Zero to Scale: Lessons from Airbnb...

High Signal: Data Science | Career | AI ·

2025/01/09

In this episode of High Signal, 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. Key topics from the conversation include: From Zero to Scale: How Elena built Airbnb’s data science function from the

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1:18:44

Episode 7: What Lies Beyond Machine Learning and AI:...

High Signal: Data Science | Career | AI ·

2024/12/19

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.Key topics from the conversation include: • From Prediction to Prescription: Why

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1:18:23

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

High Signal: Data Science | Career | AI ·

2024/12/04

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.Highlights from the discussion include: - Judgment as a Competitive Edge: Hilary emphasizes the enduring importance of human judgment in

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1:02:06

Episode 5: The Hard Truth About Building AI Systems...

High Signal: Data Science | Career | AI ·

2024/11/20

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.Highlights from the discussion include: - Bridging the C-Level and Technical Divide:

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51:16

Episode 4: How to Build an Experimentation Machine...

High Signal: Data Science | Career | AI ·

2024/11/07

Ramesh Johari (Stanford, Uber, Airbnb, and more) explores the art and science of online experimentation, especially in the context of marketplaces and tech companies.Ramesh shares insights on how organizations evolve from basic experimentation practices to becoming fast, adaptive, and self learning organizations. We dive into challenges like the risk aversion trap, the importance of learning from negative results, and how generative AI is reshaping the experimentation landscape. We also talk about

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52:12

Episode 3: Data Science Meets Management: Teamwork,...

High Signal: Data Science | Career | AI ·

2024/10/19

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

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1:00:51

Episode 2: Fooling Yourself Less: The Art of...

High Signal: Data Science | Career | AI ·

2024/10/19

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

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1:15:12

Episode 1: The Next Evolution of AI: Markets,...

High Signal: Data Science | Career | AI ·

2024/10/19

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.

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