Paul Kepley is a data science product consultant with a decade of experience applying quantitative modeling to market research and financial services, now advising at Circana after roles at IRI and Discover. He blends rigorous academic training—a PhD in Mathematics from Purdue—with hands-on forecasting work, having led credit card and student loan loss forecasting and CECL model validation during volatile economic periods. Paul excels at turning complex statistical methods into explainable, production-ready forecasts and has a background in computational research using Python and MATLAB. Based in Chicago, he brings both domain expertise in credit risk and a researcher's habit of stress-testing models under realistic scenarios.
10 years of coding experience
12 years of employment as a software developer
Doctor of Philosophy (Ph.D.), Mathematics, Doctor of Philosophy (Ph.D.), Mathematics at Purdue University
Bachelor of Arts (BA), Mathematics and Physics, Bachelor of Arts (BA), Mathematics and Physics at Washington University in St. Louis
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