Senior Bayesian Risk Modeler

A company is looking for a Senior Bayesian Risk Modeler to lead the evolution of their wildfire risk assessment platform.

Key Responsibilities

Redesign annualized risk frameworks using Monte Carlo simulation and Bayesian models to quantify uncertainty in wildfire risk estimates

Develop and validate probabilistic models that propagate uncertainty from various risk factors to final risk outputs

Optimize weather day selection algorithms and apply extreme value theory to characterize tail risks from rare weather events

Required Qualifications

Ph.D. in Statistics, Biostatistics, Applied Mathematics, or related quantitative fields preferred; a master's degree with significant experience will be considered

6+ years of experience in quantitative roles requiring sophisticated statistical modeling

Proven mastery of Bayesian inference methodology and hands-on experience with MCMC samplers

Extensive experience with Monte Carlo simulation and uncertainty quantification

Advanced Python skills and proficiency with probabilistic programming frameworks