James Chang
Data, Payment Risk Analytics
San Francisco Bay Area United States
Summary
👤
Senior🎓
Top SchoolJames Chang is a data and payment risk analytics leader with a decade of experience applying statistical modeling and machine learning to financial and payment risk problems. Currently at Uber, he oversees core rides payment fraud analytics and manages external vendor relationships, bringing production-ready models to high-volume, real-time environments. His background spans treasury modeling at Citi and risk and strategy roles at major banks where he built ALM, economic capital, credit cycle, and collections models that informed portfolio and regulatory decisions. Skilled in SQL, Python, R, SAS, Tableau and a wide range of algorithms from regression to boosting and NLP, he blends rigorous quantitative research with practical deployment. James combines an MSc in Finance and an Hon. BSc in Statistics with a track record of turning complex time-series and macro-economic signals into actionable risk controls. He’s notable for translating bank-grade risk methodology into scalable, product-facing analytics in fast-moving tech settings.
10 years of coding experience
2 years of employment as a software developer
Hon. BSc, Statistics, Hon. BSc, Statistics at University of TorontoMaster of Science (MSc), Finance, Master of Science (MSc), Finance at Simon Fraser University
Github Skills (1)
java9
Programming languages (1)
Github contributions (1)
uber/tchannel-java
May 2016 - May 2016
A Java implementation of the TChannel protocol.
Contributions:29 commits, 4 PRs, 29 pushes in 2 days
java
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