AI Agents for Bayesian Data Science

Thomas Wiecki, Founder, PyMC Labs, is the author of PyMC, one of the most popular frameworks for Bayesian modeling, and the founder of PyMC Labs, a Bayesian AI consultancy. He holds a PhD in Computational Cognitive Neuroscience from Brown University and previously served as VP of Data Science and Head of Research at Quantopian Inc., where he built and led a team of data scientists to develop a hedge fund leveraging insights from a crowd-sourced pool of 300,000 researchers. In this episode, we explore how AI agents have made Bayesian methods more accessible to non-experts. Bayesian models are useful for both forecasting and decision-making under uncertainty. These models can act as scenario simulators, making it possible to ask what-if questions about marketing, seasonality, or health interventions while exposing the mechanisms behind an outcome. We also discuss how agentic engineering has finally helped deliver on some of the original promises of data science, how to effectively embedding agents in tools like Slack or Discord to democratize access to company information, and what parts of data science still require talking with humans to understand the problem. Full episode notes Transcript Chapters (00:00) - Agentic engineering meets Bayesian decision science (05:27) - Bayesian models versus black-box prediction (10:22) - Confounders and causal mechanisms (12:41) - From notebooks to model-aware agents (15:41) - The rise of agentic interfaces (19:18) - Alchemize and verified code translation (29:49) - Agentic data science beyond the silo (34:25) - Daimon and collaborative multiplayer AI (37:43) - Verification and unsettled methods (42:53) - Parallel agents and PyMC Forecast (51:08) - The Bayesian method of software engineering (53:59) - Agents as software's primary users (57:08) - Institutional knowledge and bus-factor risk (01:03:56) - Faster research and open source (01:12:05) - Causal models for AI's future ⠀ Links from the show -------------------- Master Agentic Data Science Show Us Your Agent Skills PyMC PyMC Labs Bayesian modeling causal questions media mix modeling Daimon Alchemize PyMC Forecast prior data fitted networks NumPyro Forecast Stan JAX PyTorch ⠀ Guests ------- Thomas Wiecki, Founder, PyMC Labs Website LinkedIn GitHub Twitter ⠀ Follow the podcast ------------------- LinkedIn Threads Instagram TikTok ⠀ Follow Dan Gerlanc ------------------- X LinkedIn Threads Bluesky