Risk and Resilience Engineer

Responsibilities Risk & Resilience Modeler We are looking for an expert in risk and resilience of the built environment to help advance how physical climate risk is translated into real-world financial impacts.   Our Science teams develop world-class hazard models across a range of natural perils. In this role, you will work closely with scientists, engineers, and data experts to build sophisticated loss and resilience models that quantify what those hazards mean for buildings and infrastructure around the world.   You will develop models that translate exposure to hazards such as flood, wildfire, and wind into estimates of structural damage, repair costs, downtime, and broader economic impacts. These models are a critical link between physical and financial risk, enabling our customers to understand not only where risk exists, but what it could mean financially—and how investments in resilience and adaptation can reduce that risk.   This is a highly interdisciplinary role at the intersection of engineering, resilience, materials science, cost estimation, statistics, and data science . We are particularly interested in candidates who are comfortable solving complex technical problems where data may be incomplete, inconsistent, or scarce, and who can combine first-principles reasoning with empirical evidence and modern quantitative methods to develop defensible, scalable solutions.   https://careers.msci.com/life-at-msci   Your Key Responsibilities What You’ll Do Connect physical climate risk to financial risk by developing custom loss models that quantify impacts to buildings, infrastructure, and other assets globally, integrating them with First Street’s hazard models. Model damage, recovery, and economic impacts by developing estimates of structural damage, repair costs and timelines, downtime, and indirect impacts using approaches including engineering first principles, cost estimation, statistical methods, and machine learning. Turn imperfect data into actionable models by analyzing historical loss and observational datasets, identifying data limitations and quality-control issues, and developing technically sound approaches to address them. Validate model performance and quantify uncertainty through statistical analysis of model predictions, observational data, sensitivities, and uncertainty to ensure outputs are scientifically rigorous and decision-useful. Translate research into scalable modeling approaches by evaluating academic literature, engineering research, industry standards, and emerging methodologies and incorporating relevant insights into quantitative loss and resilience models. Characterize the global built environment by analyzing building codes, exposure datasets, construction practices, materials, occupancy types, and regional differences to inform vulnerability and loss model development across diverse geographies. Model the value of resilience and adaptation by developing property-level adaptation scenarios that allow customers to understand how protective measures can reduce damage and downtime and evaluate the potential return on investment of resilience interventions. What We’re Looking For The ideal candidate brings expertise across several disciplines rather than fitting neatly into a single technical category. Your background may include structural or civil engineering, resilience engineering, materials science, catastrophe or risk modeling, construction cost estimation, statistics, or data science .   You are comfortable moving between engineering fundamentals and large datasets, challenging assumptions, working through uncertainty, and developing practical solutions when perfect data does not exist. Most importantly, you are excited by the opportunity to build models that transform complex climate science into information that can support better financial, infrastructure, and resilience decisions.   This is an opportunity to work on technically challenging problems with