Tong Lu
Senior Research Analyst at Cubist Systematic Strategies
New York City Metropolitan Area United States
Summary
👤
Senior🎓
Top SchoolTong Lu is an experienced quantitative researcher and data scientist with 12 years building production-grade ML and investment systems across fintech and systematic trading. He led data science teams at Avant, scaling models and orgs while deploying automated, large-scale ML pipelines, then transitioned to alternative data and alpha research roles at Citadel before focusing on digital assets at Cubist. At Cubist he progressed from Research Analyst to Senior Research Analyst and is currently on garden leave under a non-compete, reflecting deep, recent hands-on work in crypto quantitative processes. His technical strengths span end-to-end model development, productionization on cloud platforms, and feature engineering from complex credit and alternative datasets. Tong holds an MS in Statistics from the University of Chicago and brings a track record of turning research into measurable business impact (e.g., substantial reductions in default and increases in funded volume). Based in the New York metro area, he combines rigorous academic training with practical deployment expertise in both consumer credit and high-frequency trading environments.
12 years of coding experience
8 years of employment as a software developer
Exchange Student Mathmatics, Exchange Student Mathmatics at National Taiwan UniversityLondon School of EconomicsMaster of Science Statistics, Master of Science Statistics at University of ChicagoBS Economics, BS Economics at Xiamen University
Github Skills (34)
portable10
gradient10
dataflow9
spark9
gbm9
xgboost9
java9
scala9
machine-learning9
distributed-systems9
boosting9
scalable9
python8
dask8
gradient-boosting8
Programming languages (3)
Github contributions (5)
FeiYeYe/xgboost
Mar 2015 - May 2016
Contributions:4 PRs, 1 comment in 1 year 1 month
distributed-learningextrememachine-learninggbdtgbrt
tonglu/allthepackages
Feb 2015 - Feb 2015
Contributions:2 pushes in 1 day
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