Adventures in Why

A Machine Learning Blog

Bob Wilson

Bob Wilson

Data Scientist



Bob Wilson is a data scientist at Netflix, where he helps entertain the world by improving content quality. Prior roles include Marketing Analytics at Meta Reality Labs, Director of Data Science (Marketing) at Ticketmaster, and Director of Analytics at Tinder. His interests include causal inference and convex optimization. When not tweaking his Emacs init file, Bob enjoys gardening, listening/singing along to Broadway musical soundtracks, and surfeiting on tacos.


  • Causal Inference
  • Convex Optimization
  • Theoretical Statistics


  • M.S.E.E. in Machine Learning, 2013

    Stanford University

  • B.S. in Aerospace Engineering, 2008

    University of Illinois, Urbana-Champaign

Recent Musings

Instrumental Variables

Data scientists at tech companies are spoiled. It’s so easy for us to A/B test everything. We have the hooks in place to easily alter some aspect of the product with minimal engineering lift, we have the sample size to get a good read in as little as a few days, and we have the data infrastructure to quickly analyze and report results.

Eglot+Tree-Sitter in Emacs 29

I’ve been an Emacs user for about 15 years, and for the most part I use Emacs for org-mode and python development. I’ve happily used Jorgen Schäfer’s elpy as the core of my python development workflow for the last 5 years or so, and I’ve been happy with it.

Compiling Emacs 29 With Tree-Sitter

I started a new job recently and took the opportunity to install a new version of Emacs. Emacs 29 includes tree-sitter and built-in eglot support, which I’ll write about some other time.


A/B Testing

Calculators for planning and analyzing A/B tests


Generalized Additive Models in Python


Orbit Propagator in Python


Homebrewed Beer Calculator

Unit Parser

Unit Parser and Conversions in Python

Other Papers

Star Identification via Computer Vision Techniques

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A Discussion of Relativistic Phenomena and Construction of Spacetime Diagrams

We discuss how the Special Theory of Relativity proceeds from the absence of an absolute definition of stationarity, as well as the observation that light travels at the same speed in all reference frames. Some interesting phenomena follow: two observers in relative motion cannot always agree on the length of an object, the time between two events, or even in what order the events occurred.

Recent & Upcoming Talks

Causal Inference and A/B Testing

Interana invited me to give a talk on A/B testing and analytics at Tinder.