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High Signal: Data Science | Career | AI

Delphina
Data Science
Machine Learning
Generative AI
Artificial Intelligence
Data-Driven Decision Making
AI Product Development
Data Intelligence
Online Experimentation
Software Development
Healthcare
AI Adoption
Causal Inference
Baseball
Self-Learning Organizations
Sports Analytics
Automation
Reels
Spatial Intelligence
Entrepreneurship
AI Development

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... more

PublishesTwice monthlyEpisodes40Founded2 years ago
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Artwork for High Signal: Data Science

Latest Episodes

Steve Tadelis, Professor of Economics at UC Berkeley and former senior economist at eBay and Amazon, joins High Signal to bridge the gap between economic theory and the high-stakes reality of data science and AI. Drawing on his experience at the fore... more

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Chris Fonnesbeck, veteran analyst for the Yankees and Mets and creator of the open-source Bayesian modeling library PyMC, joins to unpack why baseball has been a leading indicator for data science and analytics for over a century, and why builders an... more

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Noah Bruegmann, President of Data CRT, joins High Signal to discuss how to move your data function from a cost center to a strategic "value center". He explains how AI amplifies your existing data culture, the importance of "no-assistance" reporting,... more

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Jordan Morrow, SVP of Data & AI Transformation at AgileOne and the "Godfather of Data Literacy," joins High Signal to discuss the shift from being "data-driven" to becoming "AI-enabled." Jordan warns that many organizations are walking into the same ... more

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Recent Guests

Chris Fonnesbeck
Principal Data Scientist at PyMC Labs; adjoint associate professor at Vanderbilt University Medical Center
PyMC Labs; Vanderbilt University Medical Center
Episode: Episode 39: The 100-Year Lead: What Baseball Teaches Us About the Future of AI
Jordan Morrow
Senior Vice President of Data and AI Transformation
AgileOne
Episode: Episode 37: Engineered Intelligence and The Data Science Problem in AI
Dawn Woodward
Distinguished engineer at LinkedIn
LinkedIn
Episode: Episode 36: AI and the Judgment Problem in Data Science
Jeremy Hermann
CEO and co-founder of Delphina
Delphina
Episode: Episode 36: AI and the Judgment Problem in Data Science
Martin Tingley
Head of Windows Experimentation at Microsoft; former head of the Experimentation Platform Analysis Team at Netflix
Microsoft; formerly Netflix
Episode: Episode 35: Beyond Online Experimentation: Generative Software That Optimizes Itself
Benn Stancil
Expert in AI and data science
Episode: Episode 33: Why Your AI Product Will Be Obsolete in Six Months (And What To Do About It)
Cara Dailey
VP and Head of Data Strategy at Early Warning, expert in data governance and strategy within financial services
Early Warning
Episode: Episode 31: Why Data Governance In Your Org is Broken (And How to Fix It)
Chris Child
VP of Product for Data Engineering at Snowflake
Snowflake
Episode: Episode 30: The AI Paradox: Why Your Data Team’s Workload is About to Explode
Liz Costa
Chief of Innovation and Partnerships at the Behavioral Insights Team
Behavioral Insights Team
Episode: Episode 29: Why AI Adoption Fails: A Behavioral Framework for AI Implementation

Host

Hugo Bowne-Anderson
Host of the show; leads conversations on data science, AI, and governance.

Reviews

4.9 out of 5 stars from 37 ratings
  • Grounded, Smart, and Useful

    I stumbled on High Signal a few months ago and it’s quickly become one of my go-to listens. The conversations feel honest and grounded, without the usual buzzwords or surface-level takes. One episode that really stood out was the deep dive into high stakes AI systems — thoughtful, practical, and relevant to the challenges many of us are facing right now. I always walk away with something useful or a new perspective.

    Apple Podcasts
    5
    LowVariance
    United Statesa year ago
  • Very high signal on AI

    Love the episode with O’Reilly - especially how software engineering can grow in the AI era.

    Apple Podcasts
    5
    Misterv2
    United Statesa year ago

Listeners Say

Key themes from listener reviews, highlighting what works and what could be improved about the show.

High signal quality and relevance for listeners building data platforms and AI initiatives.
Audience notes that episodes balance rigor with accessible storytelling.
Deep dives into data culture and governance are consistently valuable.
Guests bring real-world experiences, not hype, with actionable takeaways.
Thoughtful, practical AI conversations that cut through buzzwords.

Chart Rankings

How this podcast ranks in the Apple Podcasts, Spotify and YouTube charts.

Apple Podcasts
#53
Austria/Technology
Apple Podcasts
#213
Russia/Technology

Talking Points

Recent interactions between the hosts and their guests.

Episode 39: The 100-Year Lead: What Baseball Teaches Us About the Future of AI
Q: What is the role of Bayesian thinking in modern baseball analytics, and how does it translate to other fields?
Bayesian thinking provides a rigorous framework for updating beliefs as new data come in, sharing strength across groups, and handling small sample sizes through hierarchical models. This approach helps quantify uncertainty and supports risk-aware decisions, a mindset that translates well to marketing, finance, and enterprise data contexts beyond sports.
Episode 39: The 100-Year Lead: What Baseball Teaches Us About the Future of AI
Q: Why is baseball uniquely suited to quantitative analysis compared to other sports?
Baseball is highly amenable to modeling because it comprises discreet, state-based events that can be treated as Bernoulli-like trials. The data are rich, observational, and allow for strong priors and hierarchical modeling across seasons, teams, and players. This structure makes it possible to separate signal from noise, build predictive models, and quantify uncertainty, which then guides decision-making.
Episode 38: Why AI Won’t Fix Your Data Culture, It Will Only Amplify It (And What To Do About It)
Q: What are the risks of relying too much on AI for important decisions, and how should governance be set up?
He emphasizes the need for baselining, context-aware analysis, and human verification, noting that AI should augment judgment, not replace it; organizations must maintain quality bars and accountability.
Episode 38: Why AI Won’t Fix Your Data Culture, It Will Only Amplify It (And What To Do About It)
Q: How can companies shift away from cost-center thinking to unlock real value from data?
Noah explains that organizations should rebrand data work as a strategic capability, focus on solving business problems with data, and demonstrate ROI through concrete decisions and profitability rather than just building pipelines.
Episode 36: AI and the Judgment Problem in Data Science
Q: How is AI impacting the speed and reliability of experimentation at scale?
AI accelerates idea generation and analysis, but it also necessitates robust evaluation, provenance, and governance to ensure that rapid experimentation yields trustworthy results.

Audience Metrics

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Frequently Asked Questions About High Signal: Data Science

What is High Signal: Data Science about and what kind of topics does it cover?

High Signal explores data science, AI, and machine learning through conversations with leading practitioners and researchers. Episodes consistently center on shaping data culture, governance, and responsible AI adoption, with practical frameworks for turning data work into measurable business value. Listeners get candid takes on data literacy, experimentation at scale, governance, and the tension between tool fever and disciplined practice, plus real-world case studies from tech giants, airlines, media, and financial services. A standout trait is its emphasis on storytelling, context, and actionable insights—helpful for teams building data platforms, guiding AI strategy, or evaluating new data tools and partnerships.

What makes this show n... more

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1. Complex Systems with Patrick McKenzie (patio11)
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3. Invest Like the Best with Patrick O'Shaughnessy
4. Freakonomics Radio
5. Software Engineering Radio - the podcast for professional software developers

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High Signal: Data Science launched 2 years ago and published 40 episodes to date. You can find more information about this podcast including rankings, audience demographics and engagement in our podcast database.

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What guests have appeared on High Signal: Data Science?

Recent guests on High Signal: Data Science include:

1. Chris Fonnesbeck
2. Jordan Morrow
3. Dawn Woodward
4. Jeremy Hermann
5. Martin Tingley
6. Benn Stancil
7. Cara Dailey
8. Chris Child

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