About the role
Company & Mission Overview: Our mission: We exist to connect climate and financial risk.
Who we are: First Street is the standard for Climate Risk Financial Modeling. For over a decade, we’ve been translating climate risk into decision-useful financial outcomes for investors, businesses, communities, and property owners worldwide. With backing from world-class firms, including Innovation Endeavors, Galvanize, General Catalyst, and others, our team has raised millions to change how the global economy thinks about climate change. Read more about our culture here and see what Climate Risk Financial Modeling is all about here . Our data: We’ve assembled leading climate scientists and economists to develop transparent, peer-reviewed methodologies to calculate the past, present, and future climate risk for properties and asset classes spanning real estate, infrastructure, and companies. Using physics-based deterministic models, we predict the likelihood of floods, wildfires, hurricanes, and other hazards at any location on Earth, along with associated damage and downtime. Our customers: We aim to incorporate climate risk data into every financial decision made today. We are relied on every day by: Institutional investors like Norges Bank Investment Management and Blackstone. Banking enterprises, including Bank of America and Fifth Third. Government bodies ranging from Fannie Mae to the US State of Connecticut. Millions of everyday users on Zillow, Redfin, Realtor.com , Homes.com , and more. Come join us and use your talents to change the world. 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 Our anticipated US base salary
