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.

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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