Summary
Jinlei Zheng is a systems-oriented quantitative and machine learning modeler with over a decade of experience building production fraud detection and NLP systems for financial services at Bank of America. With a PhD in Space Physics, he brings rigorous data-processing and physics-guided modeling skills to large, messy datasets — skills honed earlier in NASA-funded solar energetic particle prediction and flux-rope detection research that produced widely used datasets. At Bank of America he has designed and operationalized multi-channel fraud models (cards, ACH, wires, P2P) and led development of complaint-resolution NLP systems leveraging LLMs. Known for combining deep learning, tree-based methods, and strong evaluation metrics, he balances research-grade experimentation with the pragmatics of monitoring and retraining models in production. Based in New York, he uniquely blends academic rigor with enterprise delivery, often surfacing non-obvious signal patterns from heterogeneous transactional data.
10 years of coding experience
14 years of employment as a software developer
Master of Science - MS Space Physics, Master of Science - MS Space Physics at University of Chinese Academy of Sciences
Doctor of Philosophy - PhD Space Physics, Doctor of Philosophy - PhD Space Physics at The University of Alabama in Huntsville
Bachelor of Science - BS Physics, Bachelor of Science - BS Physics at Changsha University of Science and Technology