이 에피소드에 관해
Causality, Experimentation, and Marketplaces
Meet Lawrence de Geest (Zoox, ex-Lyft, ex-NBA), a former soccer player and an ex-NBA data scientist, who fell in love with marketplaces, despite the fact he hated math.
In the episode we ponder how to deal with causality when our interventions change the dynamics of the environment we intervene upon, what to do with SUTVA violations, and how to design efficient quasi-experiments.
- Why simple A/B tests fail at marketplaces
- How reversing synthetic controls logic can help us design better experiments
- Why Lawrence thinks that average treatment effect is just a snapshot of here and now
- How Magellan used data science to prove that Portugal was harvesting spices on Spanish territory
------------------------------------------------------------------------------------------------------
Video version available on YouTube: https://youtu.be/acCy16L33tU
Recorded in 2026 in San Francisco, USA.
------------------------------------------------------------------------------------------------------
About The Guest
Lawrence De Geest is an economist and data scientist at Zoox. He was previously a data scientist at Lyft and the NBA, and before joining industry, an Assistant Professor at Suffolk University, with visiting appointments at Boston College and the University of San Francisco. His main research interests are marketplaces, collective action and experimentation. Outside of work he loves biking, surfing, and playing with his dog.
Connect with Lawrence:
- Lawrence on LinkedIn: https://www.linkedin.com/in/lawrence-de-geest-21a206a/
- Lawrence's web page: https://lrdegeest.github.io/
About The Host
Aleksander (Alex) Molak is an independent machine learning researcher, educator, entrepreneur and a best-selling author in the area of causality (https://amzn.to/3QhsRz4 ).
Connect with Alex:
- Alex on the Internet: https://bit.ly/aleksander-molak
Causal Bandits Podcast
Causal AI || Causal Machine Learning || Causal Inference & Discovery
Web: https://causalbanditspodcast.com
Connect on LinkedIn: https://www.linkedin.com/in/aleksandermolak/
Join Causal Python Weekly: https://causalpython.io
The Causal Book: https://amzn.to/3QhsRz4
