Causal Python with Alex Molak
Hosted by Alex Molak
A technical podcast exploring the theory and practice of causal inference, featuring deep-dive interviews with leading academics and practitioners.
This show, also known as The Causal Bandits Podcast, bridges the gap between academic research and industry application of causal AI. Host Alex Molak engages top-tier statisticians, data scientists, and researchers in rigorous, technically-dense conversations. Episodes often take the form of a formal debate between opposing viewpoints or a deep exploration of a specific statistical method or philosophical divide.
“Unlike introductory podcasts, Causal Python dives directly into complex, niche topics like heterogeneous treatment effects and Bayesian versus frequentist debates. Its unique strength is convening world-class academics (like Judea Pearl and Bernhard Schölkopf) and senior industry data scientists for highly specific, expert-level discussions.”
Who hosts this show
The podcast is hosted by Alex Molak, an independent machine learning researcher, consultant, and educator. He is the author of the bestselling book "Causal Inference and Discovery in Python" and travels globally to record conversations with prominent minds in the field of causality. His work focuses on making complex causal methods accessible to data scientists and businesses.
Credentials & credits
- Author, "Causal Inference and Discovery in Python"
- Machine Learning Researcher and Consultant
- Founder of Lesprie.io and CausalPython.io
- International speaker on causality and AI
- Background in analytical philosophy, psychology, and neuroscience
Other ventures
- CausalPython.io (community and resources)
- Lesprie.io (corporate ML training)
- Consulting and workshops for corporate clients
What kind of podcast
- Country
- PL
- Region
- europe
When new episodes drop
- 01Predictions for One-Time Events?Jun 3, 2026 · 28s
- 02
- 03🪙 The Value of Unconstrained ScrutinyApr 11, 2026 · 46s
- 04🪤 Traps of a Weak Experimentation CultureApr 10, 2026 · 45s
- 05📈 When Short-Term Benefits Go Away :/Apr 9, 2026 · 40s
- 06Causality, Experimentation, and Marketplaces | Lawrence De Geest S2E10Apr 1, 2026 · 1h 05m
- 07
- 08
Notable episodes
- 01Do Heterogeneous Treatment Effects Exist? | Stephen Senn X Richard Hahn
A formal debate between two expert statisticians on a foundational concept, showcasing the show's distinctive format of pitting different schools of thought against each other.
- 02Causality, Experimentation, and Marketplaces | Lawrence De Geest
A clear example of the podcast bridging theory and practice, with a senior data scientist from Zoox (ex-Lyft) discussing the real-world challenges of applying causal methods in dynamic marketplaces.
- 03Causal Inference & the "Bayesian-Frequentist War" | Richard Hahn
A deep dive into the philosophical divides of modern statistics and a detailed look at a specific method (BART), exemplifying the show's technical depth.
- 04Free Will, LLMs & Intelligence | Judea Pearl
Features a conversation with Judea Pearl, a Turing Award winner and one of the most influential figures in causal inference, demonstrating the high caliber of guests on the show.
What you'll be asked on this show
Alex Molak runs a technically rigorous and structured interview. He often opens by situating the guest within a major philosophical debate in statistics (e.g., "the Bayesian-Frequentist War") or by asking them to comment on a provocative statement. He probes for deeper insight by asking about the practical challenges of implementing a specific method, connecting theoretical concepts to real-world experiments, and asking guests to define what makes a particular tool in their field "special." Molak frequently summarizes complex technical points to confirm his understanding and guide the conversation, maintaining a focused, academic tone throughout.
The show is a long-form interview format, sometimes structured as a formal debate between two guests. The host, Alex Molak, demonstrates deep domain knowledge, often framing discussions with broad philosophical questions before diving into technical specifics. Unique bits include using a Python script to decide speaker order and creating customized rap intros for guests.
Questions Alex Molak keeps coming back to
10 cataloguedIf you're going on this show as a guest, expect some version of each of these. Each note explains when Alex Molak reaches for it.
controversy
4- Q.01
“Where do you see yourself in the 'war' between different schools of thought, like Bayesians and frequentists?”
This is often an opening question to establish the guest's philosophical alignment and frame the discussion.
- Q.02
“What are your thoughts on [provocative statement or concept]?”
The host uses this to challenge the guest with a controversial idea and elicit a strong opinion.
- Q.03
“Do you believe [concept, e.g., heterogeneous treatment effects] actually exist?”
A foundational question used to kick off debates on core statistical concepts.
- Q.04
“Is it ethical to stop at the average effect if it masks harm or benefit for a subgroup?”
This question introduces an ethical dimension to a technical statistical discussion.
craft
1- Q.01
“What's special about [specific method, e.g., BART], a tool that appears often in your work?”
This question narrows the focus to a guest's specific area of expertise and preferred tools.
process
3- Q.01
“What are the main challenges you've encountered when using [specific method, e.g., synthetic controls]?”
This moves the conversation from theory to the practical difficulties of application.
- Q.02
“How do you think about generalization in the context of A/B tests and RCTs?”
This question connects a guest's theoretical work to the practical application of experimentation.
- Q.03
“Can you share your experiences testing ideas at [company], where interventions can affect the whole system?”
An opening question for industry guests to ground the discussion in real-world problems.
future
1- Q.01
“Do modern machine learning tools extend or undermine traditional statistical rigor?”
This question explores the tension between new computational methods and established principles.
personal
1- Q.01
“What's the most surprising thing you've learned about the market from your experiments?”
This question seeks a specific, memorable anecdote or insight from the guest's practical work.
Signature segments
- · The Causal Bandits Podcast
- · Greeting: "Hey Causal Bandits!"
- · Customized guest intros (including raps)
- · Using a Python script for turn-taking in debates
- · Bridging academic theory and industry practice
Topics covered repeatedly
Who gets booked here
Guests are world-renowned academics, researchers, and authors in statistics and computer science, or senior data scientists and economists from major tech companies like Zoox and Lyft. The common thread is a deep, published expertise in causal inference or its application.
- Alexander Denevon Strait of Hormuz: Causal Models for Rare Events | Alexander Denev S2E11 | CausalBanditsPodcast.com
- Lawrence de Geeston Causality, Experimentation, and Marketplaces | Lawrence De Geest S2E10
- Stephen Sennon Do Heterogeneous Treatment Effects Exist? | Stephen Senn X Richard Hahn S2E9 | CausalBanditsPodcast
- Richard Hahnon Do Heterogeneous Treatment Effects Exist? | Stephen Senn X Richard Hahn S2E9 | CausalBanditsPodcast
Where to find this show
Audience & reach
The podcast has mentioned the "Causal Data Science Meeting 2025" as a sponsor. The host also runs a consulting and corporate training business, suggesting a B2B sponsorship model targeting companies that employ data science teams and need expertise in causal methods.
Subscriber and view counts are pulled live from YouTube and re-verified on a 30-day cycle. Listener estimates for the RSS feed aren't published here unless they're host-verified.
Pitch Alex Molak
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People also ask
- What is the host's real name?
- The host is Aleksander (Alex) Molak.
- Is the podcast still active?
- Yes, the podcast releases episodes regularly, with the most recent episodes published in June 2026.
- What is the format of the show?
- It is a long-form interview show, often featuring one-on-one discussions or structured debates between two guests on technical topics related to causal inference.
- What's the difference between 'Causal Python' and 'The Causal Bandits Podcast'?
- 'Causal Python with Alex Molak' is the name of the YouTube channel, while 'The Causal Bandits Podcast' is the name of the show itself.
- Who is this podcast for?
- It's aimed at professionals and students with an existing knowledge of data science and statistics who want to learn about advanced causal inference from leading experts.
- Where can I listen to the podcast?
- The podcast is available on YouTube and major podcast platforms like Apple Podcasts and Deezer.
Built from the show's public RSS feed, YouTube, the host's own websites, and the cited sources below. Computed and AI-extracted fields are labelled. Facts only — no private info, no fabrication, no transcripts republished.
Sources & how this page was built
This page is AI-assisted, grounded in the public sources cited below, and host-verifiable. We publish facts only; we do not republish transcripts. If anything here is wrong, the host can claim and correct the page above.Model: gemini-2.5-pro · high confidence
- [01]Aleksander Molak - Oxford Lifelong Learningconted.ox.ac.uk
- [02]Causal Bandits Podcast Official Websitecausalbanditspodcast.com
- [03]Causal Python - Official Websitecausalpython.io
- [04]Aleksander Molak - Google Scholarscholar.google.com
- [05]Causal Inference and Discovery in Python - Bookgoogle.com
- [06]Causal Bandits Podcast - Apple Podcastspodcasts.apple.com
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