Kyle Colangelo
Data Scientist
New York, New York, United States
Summary
👤
Senior🎓
Top SchoolKyle Colangelo is a Data Scientist and economist with eight years of experience applying causal inference, experimentation, and machine learning to drive measurable value at scale for millions of third-party sellers. At Amazon he built production causal models (causal forests, DML, XGBoost), designed experiments robust to interference and low power, and led an A/B testing bar-raiser team that reviews 100+ experiments annually. He combines rigorous academic training (PhD in Economics) and published research with hands-on engineering—optimizing pipelines to cut runtime by 95% and delivering production products like a budget allocation optimizer for 10K+ sellers. Now at Google, he continues to bridge causal methods, ML, and product strategy, translating complex technical findings into actionable business decisions. An often-overlooked strength is his track record mentoring teams and institutionalizing experimentation standards that scale across organizations.
8 years of coding experience
Cal Poly PomonaUniversity of California, Irvine
Github Skills (2)
kubernetes9
python9
Programming languages (2)
Github contributions (5)
KColangelo/Double-ML-Continuous-Treatment
Jan 2021 - Oct 2022
Code for Colangelo and Lee (2022)
Contributions:14 commits, 25 pushes, 1 branch in 1 year 9 months
KColangelo/DDML
Jan 2020 - Apr 2020
Contributions:5 pushes, 1 branch in 2 months
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