Risk & Resilience Engineer

Team & Role Overview

We are looking for an expert in risk and resilience of the built environment. Our Science teams build world class hazard models across several perils, and this person will work with them to build world class loss models of the risk for a variety of asset types. The loss models will represent structure damages and associated downtime from exposure to natural hazards like flood, wildfire, and wind, enabling our customers to connect physical risk to financial risk.

The Risk & Resilience Modeler will have a background in a combination of engineering, materials science, resilience, cost estimation, and data science. A successful candidate will demonstrate the capability to solve technical challenges in data poor areas.

What you’ll do

• Connect climate and financial risk by developing custom loss models representing impacts to structures and infrastructure assets globally to pair with First Street’s hazard models
• Create models of structure damage, repair time, and indirect impacts using a combination of approaches including first principles of engineering, cost estimation, statistics, and machine learning
• Analyze historical loss observational data to improve model accuracy, identify quality control issues, and develop suggested remedies for identified issues
• Perform statistical analysis to validate loss model predictions and assess model uncertainties
• Conduct background research and using insights from the current state of academic literature to inform approaches in quantitative modeling
• Analyze building codes and exposure datasets to identify common construction practices globally to inform loss model section
• Create property level adaptation scenarios that enable customers to understand the return on investment of personal property protections

What you’ll need

• Ph.D. (preferred) or Master’s degree with 3 years experience in structural engineering, civil engineering, operation research, or a related field
• Strong background in vulnerability developments, statistics, and/or quantitative analytics
• Hands-on experience in developing risk models for buildings or infrastructure systems using machine-learning models or statistical methods
• Experience working with multi-hazard data, catastrophe models, building level damage data, and construction cost estimation data
• Expertise using scripted languages like Python
• Expertise in a science-based approach with a high degree of concern for reliability, accuracy and reproducibility

What will make you stand out

• Experience in developing scalable and generalized catastrophe risk models
• Strong publication record
• Proficiency with source control platforms such as Git
• Research experience in the latest resilience modeling, technical guidelines, etc.
• ML/AI experience
• Expertise with big data analysis in high performance compute environments, either on premises or on cloud platforms including AWS, GCP, and/or Azure
• Hands on experience in building loss models from scratch

Pay & Benefits

Our anticipated US base salary compensation range for this role is $90,000-$125,000 plus competitive benefits package, which includes bonus, 401(k) with company match, paid time off, paid parental leave, and comprehensive health benefits. Actual compensation will vary depending on factors such as work location as well as additional factors such as a candidate’s qualifications, skills, experience, competencies, and relevant education.