Job Type: Full-time, Remote
Location: United States
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.
Team & Role Overview:
We are looking for a Scientist with expertise in data analysis and modeling of wildfires and the fire environment, strong machine learning and data science skills, and demonstrable experience working with remotely sensed data sources to join our team. This person will need to have a Ph.D. in wildfire science or a related field and ideally will have postdoctoral professional experience. In addition to technical skills and subject matter expertise, they will also have the ability to lead projects and collaborate closely with other scientists.
What you’ll do:
Collaborate with our wildfire, climate science, and data science teams to build global wildfire risk models.
Estimate wildfire fuels using a combination of in situ and remotely sensed data.
Introduce innovative methods to improve the wildfire risk model performance and assess fire risk at a 30m spatial resolution.
Expertise in the formulation and use of FM40 fuel classification for Rothermel-based wildfire behavior models.
Work with the team to manage fire model production, quality control and ongoing evaluation/validation efforts.
Identify and develop new data inputs and methodological improvements for inclusion into the First Street Wildfire Model.
What you’ll need:
Ph.D. in wildfire science or a related subject, with experience in fire behavior modeling and quantitative analysis of the fire environment.
Strong foundation in understanding of modeling fire behavior and wildfire processes; experience modeling fuels layers and vegetation would be particularly desirable.
Strong understanding of statistics and Machine Learning and how they can be applied to vegetation, fuels, wildfire and climate models.
Expertise with remotely sensed data, big data analysis, large-capacity processing workflows, and cloud computing.
Expertise in various fire behavior modeling methods, especially Rothermel-based models (e.g., ELMFIRE or FSIM) or similar modeling frameworks.
Experience with wildfire behavior and risk modeling in the Wildland Urban Interface (WUI).
Expertise in probability and statistics related to fire ignition analysis.
Expertise using both compiled and scripted languages (e.g., Matlab, Python, UNIX shell, C++, Fortran, and/or SQL) and GIS software (e.g., QGIS and ArcGIS) to efficiently analyze outputs.
Ability to work in a fast-paced team environment.
What will make you stand out:
Experience authoring peer-reviewed scientific publications in areas related to wildfires and fire risk.
Skill/Experience developing a variety of satellite-based wildfire fuel maps for use in Rothermel-based fire behavior models.
Skill/Experience in creating/evaluating/validating fire behavior models and their inputs, and quantitatively evaluating model performance.
Prior experience in a fast-paced startup environment
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
