Philipp Baumann
Applied Scientist II at Amazon
Amsterdam, North Holland, Netherlands
Summary
👤
Senior🎓
Top SchoolPhilipp Baumann is an applied scientist with eight years of experience at the intersection of machine learning, statistics and causality, currently working as Applied Scientist II at Amazon. He holds a Ph.D. in Econometrics and Machine Learning from ETH Zurich and recently completed a postdoc focused on causal demand forecasting in collaboration with industry. A winner of Citadel’s Global PhD Datathon, he combines strong methodological foundations with practical impact, evidenced by publications in leading conferences and journals across ML, statistics and causal inference. His work spans both methodological development and applied forecasting, and he has contributed reproducible software and methodological code linked from his academic profile. Based in Amsterdam, he brings experience translating rigorous research into production-relevant solutions for large organizations.
8 years of coding experience
6 years of employment as a software developer
Master of Science - MS, Statistics, Master of Science - MS, Statistics at Ludwig-Maximilians-Universität MünchenBachelor's degree, Economics, Bachelor's degree, Economics at Universität Zürich | University of ZurichDoktor (Ph.D.), Econometrics and Machine Learning, Doktor (Ph.D.), Econometrics and Machine Learning at ETH Zürich
Github Skills (4)
lme48
criterion4
inference2
python1
Programming languages (2)
Github contributions (5)
PFMB/selfmade
Mar 2019 - Nov 2019
SELective inFerence for Mixed and Additive model Estimators
Contributions:6 PRs, 39 pushes, 1 comment in 8 months
additiveestimatorsinferenceselective
PFMB/causalchall
Sep 2022 - Mar 2023
Contributions:2 pushes, 1 branch in 6 months
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