Oleg Sofrygin

Sr Applied Scientist at Uber

San Francisco, California, United States
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Summary

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Senior
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Oleg 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.
code12 years of coding experience
job7 years of employment as a software developer
bookPhD Biostatistics & Bioinformatics, PhD Biostatistics & Bioinformatics at University of California, Berkeley
bookPost-Bac Extension School Health Careers Program, Post-Bac Extension School Health Careers Program at Harvard University
bookMathematics / Computer Science, Mathematics / Computer Science at Ural State University
bookMA Mathematics, MA Mathematics at Brandeis University
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Stackoverflow

Stats
151reputation
1kreached
0answers
1question
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Github Skills (60)

causal10
sem10
r-package10
stochastic10
linear-models10
mixed-models10
meta-analysis10
longitudinal-data10
r9
dataflow9
portable9
xgboost9
causal-inference9
java9
gradient9

Programming languages (4)

JuliaRC++Rez

Github contributions (5)

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osofr/growthcurveSL

Sep 2016 - Aug 2017

Contributions:123 commits, 104 pushes in 10 months
imputationpythonsuperlearner
osofr/condensier

May 2017 - Jan 2019

Contributions:59 commits, 19 PRs, 46 pushes in 1 year 7 months
parametricconditionalnon-parametricdensity-estimationestimation
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Oleg Sofrygin - Sr Applied Scientist at Uber