Hongwei Wu
Data Scientist
New York, New York, United States
Summary
👤
Senior🎓
Top SchoolHongwei Wu is a data scientist with 12 years of applied research and development experience spanning central banking, financial regulation, insurance, and academia. He brings deep quantitative expertise—Bayesian inference, MCMC, Kalman/Hamilton filters, VAR and Markov-switching models—and a strong machine learning background in NLP, deep learning, clustering and dimensionality reduction. He has led advanced analytics teams at FINRA and built HPC-parallelized econometric and DSGE models at the Federal Reserve, then transitioned to industry roles at AIG and Citi where he applies research-grade methods to real-world risk and text-analytics problems. A published researcher who once switched fields and produced a high-impact journal paper within six months, he blends rigorous theory with production coding (C++, Python) and practical optimization for large-scale problems. Based in New York, he is known for turning complex, irregular statistical problems into scalable solutions and for communicating technical results clearly to diverse stakeholders.
11 years of coding experience
15 years of employment as a software developer
Ph.D, Electrical Engineering, Ph.D, Electrical Engineering at University of Southern CaliforniaHigh SchoolB.Eng., Electrical Engineering, B.Eng., Electrical Engineering at Tsinghua UniversityGithub contributions (5)
parb220/equal_energy_generic_interface
Jan 2015 - Apr 2016
Contributions:41 pushes, 9 branches in 1 year 3 months
parb220/KK
May 2014 - Oct 2014
Contributions:38 commits in 4 months
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