Pasha Stetsenko
Member Of Technical Staff at Omnifold
Menlo Park, California, United States
Summary
🤩
Rockstar🎓
Top SchoolPasha Stetsenko is a Member of Technical Staff and PhD economist turned software engineer with a decade of experience building scalable statistical and ML systems for companies from startups to Facebook and Google. He combines deep econometrics and time-series expertise with hands-on backend engineering—contributing significant core functionality to widely used open-source projects like H2O and datatable. At Keystone he engineered pipelines for truly massive datasets (petabyte-scale) and at Machinify and H2O designed robust statistical models for anomaly detection and business metrics. Comfortable across Python, R, Stata, SQL and web stacks (PHP/Hack, JS, React), he bridges rigorous modelling with production-grade code and security-conscious system design. A top Project Euler performer and contributor to performance-sensitive libraries, he brings a rare mix of theoretical depth and pragmatic implementation skill.
10 years of coding experience
10 years of employment as a software developer
Ukrainian Physics and Mathematics LyceumMaster General & Applied Physics, Master General & Applied Physics at Moscow Institute of Physics and Technology (State University) (MIPT)Master Economics, Master Economics at New Economic SchoolPhD Economics, PhD Economics at Stanford University
Ukrainian, Russian, English
Stackoverflow
6,428reputation
900kreached
58answers
13questions
indexing
top-1%
dictionary
top-5%
python
top-5%
Github Skills (45)
sprite10
flutter10
c-language10
python10
api-design10
flutter-apps10
r10
c1110
data-parsing10
indexing10
render10
java10
c1710
javas10
performance-optimization10
Programming languages (17)
Github contributions (5)
h2oai/datatable
Mar 2017 - Sep 2021
Role in this project:
Back-end Developer
Back-end DeveloperContributions:10 releases, 308 reviews, 1705 commits in 4 years 6 months
Contributions summary:Pasha primarily contributed to the implementation of core functionalities within the datatable library, specifically adding new reducer functions such as `cov()` and `corr()`, and refactoring existing binary operators to utilize virtual columns. They were also involved in general code cleanup, including improvements to documentation and the handling of string columns. The changes indicate a focus on improving the performance and functionality of the library's core data manipulation capabilities.
data-analysispythonftrltabular-datadimensional
h2oai/h2o-3
May 2016 - Aug 2018
H2O is an Open Source, Distributed, Fast & Scalable Machine Learning Platform: Deep Learning, Gradient Boosting (GBM) & XGBoost, Random Forest, Generalized Linear Modeling (GLM with Elastic Net), K-Means, PCA, Generalized Additive Models (GAM), RuleFit, Support Vector Machine (SVM), Stacked Ensembles, Automatic Machine Learning (AutoML), etc.
Role in this project:Back-end Developer & Security Engineer
Back-end Developer & Security EngineerContributions:658 commits, 250 PRs, 797 pushes in 2 years 2 months
Contributions summary:Pasha contributed to the H2O-3 repository by implementing new functionalities and performing code improvements and fixes. The contributions involve modifying the isBinary() method in Vec.java and the translation of property names in Java REST API bindings. Additionally, the user added a new endpoint for handling the LATEST prefix in RequestServer.java. These changes show the user's involvement in enhancing the project's functionality and security features.
xgboostgampythonk-meansautoencoders
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