I am currently a Data Scientist and Bayesian Statistician at Game Data Pros where I design and build production platforms for large scale experimentation, revenue optimization, promotional pricing, and personalization in mobile and console games. My general career interests center around the development and application of Bayesian inference, decision theory, reinforcement learning, and experimental design in industry.
I have extensive experience working both independently and in collaboration with colleagues to design and build production quality inferential systems, working on experimentation and ad platforms, and modeling complex data structures to provide insights necessary to answer questions and inform decisions in business and academia. My core skills include experimental design, advanced data analytics, process automation, R, Stan, Python, and a deep expertise in Bayesian statistics, decision theory, and causal inference.
In a past life, I was a PhD Candidate in the Department of Political Science at the University of North Texas where I applied Bayesian inference and computational statistics to analyze how institutions shape individuals’ attitudes, decisions, and behavior. I have two years of experience teaching undergraduate courses in statistics and causal inference for political research, American political institutions, and mass political behavior.