Terry Leitch is a founder and former front-line quantitative finance executive with 25+ years designing and governing derivatives, hedging, and risk models across banks, insurers, and corporates. He now leads ai-focused ventures (aequum.ai) and ruxton.ai as Chief Data Scientist, applying machine learning to fraud detection, Swap Data Repository analytics, and aviation finance risk products used by Marsh, CFTC, and major banks. His background spans senior roles at AEGON, Genworth, Boeing and Bank of America, plus academic appointments teaching ERM and coding in R/Python at Columbia and Johns Hopkins. Terry combines deep applied math and financial engineering training with hands-on software and cloud implementations (AWS, Docker, parallel XGBoost), and holds a patent on an equity hedging process. Colleagues describe him as a pragmatic builder who translates complex regulatory and market data into deployable models and licensed software used in real-world insurance and asset-transfer programs.
11 years of coding experience
14 years of employment as a software developer
Master of Business Administration (M.B.A.), Master of Business Administration (M.B.A.) at London Business School
M.S. Applied Math, M.S. Applied Math at Northwestern University
Graduate Certificate Financial Engineering, Graduate Certificate Financial Engineering at Columbia Engineering
A.B. Mathematics, A.B. Mathematics at University of Chicago
A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.
Contributions:32 commits, 31 pushes in 1 year 1 month
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