Risk & Resilience Modeler

Who we are: First Street is the standard for Climate Risk Financial Modeling. We use transparent and peer-reviewed methodologies to calculate the past, present, and future climate risk for every property in the world. We started working with the world’s leading climate scientists to create groundbreaking, climate-adjusted, property specific models over 8 years ago and haven’t stopped. 

Our mission: We exist to connect climate and financial risk. 

Our data: We create physics-based, deterministic models of flooding, wildfire and hurricanes, and advanced statistical models of extreme heat, air quality, drought, hail, severe convective storms, winter storms, and more. All of this data is used to create property-level financial risk metrics and macroeconomic variables to quantify the impacts of climate, property by property.

Our customers: We empower governments at the highest levels to make smart regulations, businesses to avoid bad investments, and everyday Americans to understand their personal risk from climate change. We are relied on every day by:

• Agencies ranging from the U.S. Department of Treasury to Fannie Mae

• The world's biggest banks such as Bank of America and Wells Fargo 

• Institutional investors like Nuveen and Blackstone 

• Millions of everyday users on Zillow, Redfin, Realtor.com, Homes.com, and more 

We believe:  With the right data, we can identify the problems, avoid bad investments, and implement solutions. This is why we have invested tens of millions of dollars into our science, data, people, and products and have raised tens of millions more to move even faster. Read more about our culture here and see what Climate Risk Financial Modeling is all about here. 

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

How we work: 

• Impact: We only focus on things that move the needle 

• Drive: We are driven by the role we play in connecting climate and financial risk 

• Ownership: This is our company and we act accordingly

• Urgency: We move quickly because the world depends on it 

• Resilience: We have a growth mindset in all that we do

What we offer: 

• Competitive salary commensurate with experience 

• Ownership interest in the company via Employee Stock Option Plan 

• Hybrid Schedule with in-office work days on Monday, Wednesday and Thursday 

• 15 vacation days along with 5 days for winter break office closure, 8 statutory company holidays, and 10 sick days 

• Health benefits covered at 100% for employee or a significant contribution for family plans 

• Vision and dental benefits with partial employee contribution

• 12 weeks of paid parental leave 

• Access to One Medical, Teledoc, HealthAdvocate, Kindbody, and Talkspace

• Company 401k program 

• Commuter benefits 

• Life Insurance

• Tech startup environment 

• Weekly team meals and an office stocked with coffee and snacks 

• Working on the world’s biggest issue with other passionate professionals 

We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.