Bayesian thinking in work and life, ad attribution models and A/B testing, machine learning@Foursquare - Max Sklar - the data scientist show050

Max Sklar is an independent engineer and researcher. Previously, he was an engineering and Innovation Labs Advisor at Foursquare after 7 years at the company as a machine learning engineer. Previously, he has worked on Ad Attribution, recommendation engine, ratings. He is the host of The Local Maximum podcast. Max studied CS from Yale, and holds a Master degree in information systems from New York university. If you like the show subscribe to the channel and give us a 5-star review. Subscribe to Daliana's newsletter on www.dalianaliu.com/ for more on data science. Daliana's LinkedIn: https://www.linkedin.com/in/dalianaliu/ Daliana's Twitter: https://twitter.com/DalianaLiu Max's Linkedin: https://www.linkedin.com/in/max-sklar-b638464/ Max’s website: localmaxradio.com/about Interviews he mentioned during the podcast: Andrew Gelman, Statistics at Columbia University Shirin Mojarad on Causality Johnny Nelson on Free Speech and Moderation online Stephanie Yang talking about Foursquare's Venue Rating System Dennis Crowley: on Labs, on Innovation Sophie Carr (Bayesian Mathematician) Will Kurt (Bayesian) Marsbot for Airpods Other Episodes Mentioned Bayesian Thinking P-Hacking Interview on Learn Bayesian Statistics Highlights: (0:00) Intro (00:01:23) from computer science to machine learning (00:05:35) Bayesian methods in rating system (00:14:53) how to choose a Bayesian prior (00:20:10) how to deal with p-hacking (00:26:57) causality model in ad attribution (00:35:20) Bias-correction methods (00:45:43) negative lift in advertising (00:51:05) unexpected consumer behaviors (00:52:08) why he decided not to climb the "engineer ladder" (00:56:46) the challenges of having 5 managers in a year (01:01:38) using the 3rd-party software vs building his own (01:04:18) how he approaches ML problems (01:07:51) his tech stack (01:09:25) his advise on learning machine learning (01:12:40) projects he is working on (01:17:10) Bayesian for his life decisions (01:22:00) how writing helps him (01:23:48) the confusion, stress and excitement in his career