Summary
Paul Johnson is an experienced data scientist and technical leader who transitioned from academia to industry and now runs his consulting firm, Data Adjacent LLC, offering rapid-response fixes for "almost working" software and analytics systems. With 14+ years in applied high-performance computing and machine learning—managing a 60-node cluster, deploying services on Azure, and leading ML Ops at H&R Block—he brings pragmatic Linux and cloud skills to production challenges. A former professor and research center director, he combines deep statistical expertise (regression, hierarchical and latent variable models, SEM) with hands-on engineering. He has published across game theory, social choice, agent-based modeling, and Monte Carlo methods, and is comfortable stepping into urgent roles to bring stranded projects to life. Unusually for a consultant, he pairs academic rigor and teaching experience with operational chops in cluster, cloud, and reproducible data-science tooling.
14 years of coding experience
8 years of employment as a software developer
Doctor of Philosophy - PhD, Political Science, Doctor of Philosophy - PhD, Political Science at Washington University in St. Louis
Master of Arts - MA, Political Science, A, Master of Arts - MA, Political Science, A at University of Iowa