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Today we’re joined by Sean Taylor, Staff Data Scientist at Lyft Rideshare Labs. We cover a lot of ground with Sean, starting with his recent decision to step away from his previous role as the lab director to take a more hands-on role, and what inspired that change. We also discuss his research at Rideshare Labs, where they take a more “moonshot” approach to solving the typical problems like forecasting and planning, marketplace experimentation, and decision making, and how his statistical approach manifests itself in his work. Finally, we spend quite a bit of time exploring the role of causality in the work at rideshare labs, including how systems like the aforementioned forecasting system are designed around causal models, if driving model development is more effective using business metrics, challenges associated with hierarchical modeling, and much much more. The complete show notes for this episode can be found at https://twimlai.com/go/486. Subscribe: Apple Podcasts: https://tinyurl.com/twimlapplepodcast Spotify: https://tinyurl.com/twimlspotify Google Podcasts: https://podcasts.google.com/?feed=aHR0cHM6Ly90d2ltbGFpLmxpYnN5bi5jb20vcnNz RSS: https://twimlai.libsyn.com/rss Full episodes playlist: https://www.youtube.com/playlist?list=PLILZm3MRkvH83C46bZ4rPmB-jKWBltWkP Subscribe to our Youtube Channel: https://www.youtube.com/channel/UC7kjWIK1H8tfmFlzZO-wHMw?sub_confirmation=1 Podcast website: https://twimlai.com Sign up for our newsletter: https://twimlai.com/newsletter Check out our blog: https://twimlai.com/blog Follow us on Twitter: https://twitter.com/twimlai Follow us on Facebook: https://facebook.com/twimlai Follow us on Instagram: https://instagram.com/twimlai