Han Mei is a Senior Analytics Consultant based in New York with nine years of experience applying statistics and NLP to TMT and financial markets. Holding a Master’s in Statistics from Columbia, Han has built production-ready analytics and sentiment models—from Word2Vec and TF-IDF pipelines to RNNs and BERT—used for fake-news detection and to inform trading signals. At FTI Consulting Han translates complex technical analyses into actionable insights for clients, drawing on prior quantitative research at QMA and operations experience at BNP Paribas. A pragmatic coder and researcher, Han has also quantified prenatal exposure effects in academic research, reflecting a rare blend of rigorous causal inference and applied machine learning.
9 years of coding experience
3 years of employment as a software developer
Bachelor's degree, Mathematics and Economics, Bachelor's degree, Mathematics and Economics at New York University
Master's degree, Statistics, Master's degree, Statistics at Columbia University in the City of New York
Contributions:59 PRs, 43 pushes, 3 branches in 4 months
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