Qinwen Zhai
Quant Associate
New York, New York, United States
Summary
👤
Senior🎓
Top SchoolQinwen Zhai is a New York-based quantitative finance professional with eight years of experience spanning trading, fund modeling, and research analytics. He holds a Master’s in Computational Finance from Carnegie Mellon and a multi-disciplinary BA from HKUST in Mathematics, Economics, and Computer Science, with an economics exchange at Columbia. As a Quant Associate at Goldman Sachs, he applies advanced quantitative methods to finance problems, after previously leading fund modeling and equity derivatives trading analysis at GS and JPMorgan. His research background includes econometric work on organ donation policy and building large investor databases for VC studies, showcasing his ability to derive insights from diverse datasets. An active developer, he has delivered web projects for a nonprofit portfolio at The Valley Fund and maintains a GitHub presence focused on quant-driven tooling and practical finance solutions.
8 years of coding experience
1 year of employment as a software developer
Exchange program, Economics, Exchange program, Economics at Columbia University in the City of New YorkMaster's degree, Computational Finance (aka. Financial Engineering/MFE), 4.03/4.3, Master's degree, Computational Finance (aka. Financial Engineering/MFE), 4.03/4.3 at Carnegie Mellon University - Tepper School of BusinessHong Kong University of Science and Technology (HKUST)
English, Chinese, Chinese
Github Skills (1)
jekyll4
Github contributions (3)
Chelsea-Zhai/CUSPEI
Jul 2017 - Mar 2020
Contributions:4 pushes, 1 branch in 2 years 8 months
Chelsea-Zhai/Chelsea-Zhai.github.io
Jul 2017 - Jul 2017
Contributions:8 pushes, 1 branch in 6 days
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