Senior Research Scientist - Risk

What you'll do

• Contribute to applied research on infrastructure risk and resilience, and set standards for risk modeling, uncertainty quantification, and decision-making.
• Develop predictive models for equipment damage, vegetation failure, outages, and wildfire risk; quantify the operational and economic effects of resilience investments.
• Assess the value of additional data, inspections, and devices using empirical and analytical methods.

What they ask for

• PhD in statistics, applied mathematics, physics, computer science, operations research, or engineering, or a comparable record of original research and applied technical work.
• Demonstrated ability to independently define and execute a substantial research agenda, evidenced by influential publications, patents, or production systems.
• Expertise in probabilistic modeling, uncertainty quantification, model validation, scientific computing, and decision-making with incomplete information.
• Substantial experience modeling operational systems.

Nice to have

• Experience in insurance or catastrophe modeling, weather prediction or climate hazards, power-system outages, or reliability engineering.

Pay

$180K – $220K (base salary); equity offered, amount unspecified

AI focus

The role develops predictive and decision models for infrastructure risk, reliability, and resilience; it does not specify AI or machine-learning work.