Oleg Sofrygin
Sr Applied Scientist at Uber
San Francisco, California, United States
Summary
👤
Senior🎓
Top SchoolOleg Sofrygin is a senior applied scientist in San Francisco with 12 years of experience specializing in causal inference on networks, statistical efficiency theory, and high-performance machine learning for large-scale health data. He combines rigorous academic training (PhD in Biostatistics from UC Berkeley) with applied work at Kaiser Permanente and Uber, developing open-source statistical software and cutting-edge estimators that bridge theory and production. His work spans deep-learning NLP on EMRs, adversarial and meta-learning approaches to improve estimator performance, and efficient computation for network-dependent data. Known for translating semi-parametric causal methods into practical tools, he brings uncommon depth in both mathematical foundations and scalable implementation.
12 years of coding experience
7 years of employment as a software developer
PhD Biostatistics & Bioinformatics, PhD Biostatistics & Bioinformatics at University of California, BerkeleyPost-Bac Extension School Health Careers Program, Post-Bac Extension School Health Careers Program at Harvard UniversityMathematics / Computer Science, Mathematics / Computer Science at Ural State UniversityMA Mathematics, MA Mathematics at Brandeis University
Stackoverflow
151reputation
1kreached
0answers
1question
Github Skills (51)
sem10
r-package10
survival10
r10
tuning-parameters10
statistics10
machine-learning10
ensemble-learning10
causal-inference10
grid-search10
regression10
longitudinal-data10
data-science9
xgboost9
flux9
Programming languages (4)
Github contributions (5)
osofr/growthcurveSL
Sep 2016 - Aug 2017
Contributions:123 commits, 104 pushes in 10 months
imputationpythonsuperlearner
osofr/tmlenet
Jun 2015 - Aug 2017
Targeted Maximum Likelihood Estimation for Network Data
Contributions:1 release, 141 commits, 2 PRs in 2 years 2 months
maximumnetwork-datamaximum-likelihood-estimationmaximum-likelihoodestimation
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