Summary
Benjamin Leroy is a senior data scientist blending rigorous statistical research with practical analytics in apparel supply chains. With a Ph.D. in Statistics from Carnegie Mellon University (supervised by Chad Schafer), his work centered on simulator-enabled conformal prediction and uncertainty quantification in machine learning. He currently applies his expertise at Nike in Portland, leading commercial analytics, supply chain data science, and global sourcing initiatives. He emphasizes robust, reproducible modeling and has contributed to multiple R and Python packages to promote best practices in coding and data science workflows. Benjamin's academic training spans UC Berkeley and CMU, with a strong foundation in statistics and applied mathematics, and he brings a decade of experience bridging research and production systems. Outside of daily modeling, he enjoys turning complex data into smart visualizations that reveal trends and risks.
10 years of coding experience
9 years of employment as a software developer
Bachelors in Statistics, Bachelors in Applied Mathematics, Statistics, 3.95/4.0, Bachelors in Statistics, Bachelors in Applied Mathematics, Statistics, 3.95/4.0 at University of California, Berkeley
Associate of Arts - AA, Mathematics (AA) and Economics (AA), 3.89/4.0, Associate of Arts - AA, Mathematics (AA) and Economics (AA), 3.89/4.0 at Santa Rosa Junior College
Masters, Statistics, Masters, Statistics at Carnegie Mellon University