Chris Farrell
Data Scientist
San Francisco Bay Area United States
Summary
👤
Senior🎓
Top SchoolChris Farrell is a data scientist and machine learning engineer with 12 years of experience building production ML systems and driving best practices to deliver measurable company value. Based in the San Francisco Bay Area, he has led ML and ads teams at Yelp, shipped models at Cash App, and currently applies his expertise at Faire. His background spans from hands-on feature engineering and model deployment to tech leadership and mentoring, informed by a PhD in physics where he analyzed petabytes of collider data and optimized distributed workflows. He took a two-year sabbatical to recharge and likely explore independent projects, reflecting a thoughtful approach to career pacing. Comfortable across Python, C++, and cloud deployments, Chris blends deep research rigor with pragmatic engineering to move experiments into reliable production.
12 years of coding experience
16 years of employment as a software developer
Doctor of Philosophy (PhD), Physics, Doctor of Philosophy (PhD), Physics at University of Califonia, Los AngelesBachelor of Science (B.S.), Physics, Bachelor of Science (B.S.), Physics at University of Florida
Github Skills (52)
portable10
xgboost10
dataflow10
machine-learning10
gradient10
boosting10
spark9
gbm9
java9
gradient-boosting9
python9
scala9
distributed-systems9
dask9
scalable9
Programming languages (3)
Github contributions (5)
cpfarrell/teaser-league-backend
Nov 2017 - Sep 2018
Contributions:27 commits, 4 PRs, 21 pushes in 9 months
cpfarrell/xgboost
Aug 2019 - Jan 2020
Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C++ and more. Runs on single machine, Hadoop, Spark, Flink and DataFlow
Contributions:9 pushes, 2 branches in 4 months
pythonflinkfeature-storedataflowgbm
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