Summary
Justin N is a Head of Quantitative Research and Ph.D. who blends a decade of academic rigor in international relations with hands-on industry analytics, including roles at Moody’s, Palantir, Booz Allen, and asset management firms. He builds and deploys advanced game-theoretic and machine-learning solutions—spanning mechanism design, stochastic/dynamic games, neural nets, SVMs, random forests, and adaptive LASSO—to solve strategic problems in conflict, proliferation, and finance. His work has produced large-scale, novel datasets (millions of observations) and bespoke algorithms that improved model performance and corrected selection bias in international conflict and alliance studies. Equally fluent in Python and R tooling (PyTorch, Scikit-learn, Pandas, ggplot/Seaborn) and SQL databases, he translates complex theory into production-ready analytics for decision-makers. Based in Washington, D.C., he combines policy expertise with quantitative product delivery, often revealing counterintuitive incentives in strategic settings.
8 years of coding experience
12 years of employment as a software developer
Bachelor's Degree, Economics & Political Science (Magna Cum Laude), Bachelor's Degree, Economics & Political Science (Magna Cum Laude) at Rutgers University-New Brunswick
Doctor of Philosophy (Ph.D.), Political Science, Doctor of Philosophy (Ph.D.), Political Science at University of Rochester