Simon Ejdemyr – Data Scientist
Things I do
I'm a data scientist and engineer building tools for decision
making and strategy. Since 2020, I've been at Netflix focusing
on experimentation and causal inference.
My background is in computational social science. Although I use
a range of quantitative methods in my work, I believe the best
insights and predictions are formed when large-scale data and
automation are married with careful human judgement and curation.
I'm from Sweden 🇸🇪, where I both worked in a warehouse and
enjoyed a short pro soccer career before going to the US for
college and a PhD. I'm just about to move to Los Angeles with my
wife, son, and daughter. My last name is pronounced AY-duh-meer.
Feel free to connect on
Things I do
- Build products and tools to make sense of complex data,
resulting in faster and higher-quality decision making
- Design systems for experimentation (randomized controlled
trials, A/B testing) and observational causal inference
- Develop, prototype, and productize large-scale machine
learning and inference models based on analytical solvers or
(Bayesian) probabilistic programming
- Use Python, R, SQL, bash, Stan, and more; and contribute to
and design APIs
- Like to keep things
as simple as possible, but not simpler, balancing
theoretical rigor and practical concerns
- Enjoy teaching and mentoring (in 2016 I won Stanford's Centennial Teaching
A few things I've published in academia
Framework for Generalization and Transportation of Causal
Estimates Under Covariate Shift. MIT CODE, with Apoorva
Lal and Wenjing Zheng.
Decision Making at Netflix. Netflix Tech Blog, with
Martin Tingley and others.
Low-latency Multivariate Bayesian Shrinkage in Online
Experiments. MIT CODE, with Matthew Wardrop and Martin
4 Keys to Using Machine Learning for Campaign Measurement.
Facebook IQ blog.
Do Elections Improve Constituency Responsiveness? Evidence from U.S. Cities.
Political Science Research and Methods, with Darin Christensen.
Segregation, Ethnic Favoritism, and the Strategic Targeting
of Local Public Goods. Comparative Political Studies,
with Eric Kramon and Amanda Lea Robinson.
Global, Regional, and National Levels and Trends in Under-5
Mortality Between 1990 and 2015, with Scenario-based
Projection to 2030. The Lancet, with UNICEF colleagues.
At Stanford I taught classes in applied statistics, for which I
developed a number of R tutorials. While likely out of date,
I've heard some are still useful.