Summary
Mark Risser is a staff scientist and climate statistician with 11 years of experience applying Bayesian modeling and computational data science to quantify climate change impacts. At Berkeley Lab he translates complex climate datasets into robust statistical inferences, drawing on a Ph.D. in Statistics from The Ohio State University and postdoctoral work in the CASCADE program. He combines academic rigor—teaching and lecturing at UC Berkeley’s Department of Statistics—with practical consulting experience to produce reproducible, decision-relevant analyses. Skilled in data analysis, climate science, and student development, he bridges research and application to inform policy and scientific understanding. Based in Brentwood, Tennessee, he brings a rare mix of classroom mentorship and laboratory-scale modeling, often emphasizing uncertainty quantification and Bayesian approaches that reveal insights not obvious from raw climate outputs.
11 years of coding experience
4 years of employment as a software developer
Doctor of Philosophy (Ph.D.), Statistics, Doctor of Philosophy (Ph.D.), Statistics at The Ohio State University
Bachelor of Science (BS), Mathematics, Bachelor of Science (BS), Mathematics at Eastern Mennonite University