Victor Zhorin is a Senior Data Scientist based in Chicago with 11 years of experience translating complex data into actionable products, currently leading advanced mortality modeling at LexisNexis Risk Solutions. He combines a strong academic foundation—a PhD in theoretical solid-state physics and an MBA in analytic finance—with deep research chops in climate-economics, game-theoretic models, and high-dimensional algorithm design. His work spans building robust stochastic models, uncertainty quantification using Chernoff entropy, and tensor-based numerical algorithms for moral hazard and adverse selection problems. Victor has a track record of turning large, heterogeneous datasets into decision-ready models for insurance, finance, and policy, and has applied numerical methods to pricing convertible securities early in his career. Colleagues describe him as someone who builds new things that work: marrying rigorous theory with pragmatic engineering to create novel product lines. An unexpected throughline is his blend of solid-state physics software development and modern data science, which gives him unusual strength in numerical computing and algorithmic innovation.
11 years of coding experience
17 years of employment as a software developer
Master of Business Administration Analytic Finance Economics Entrepreneurship, Master of Business Administration Analytic Finance Economics Entrepreneurship at The University of Chicago Booth School of Business
Doctor of Philosophy (Ph.D.) Theoretical Solid-State Physics, Doctor of Philosophy (Ph.D.) Theoretical Solid-State Physics at Kuban State University (KubSU)
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