Sr. Data Scientist

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 a Senior Data Scientist with experience working in Earth Science to join our Data Science/Data Engineering team. It's never been more important that finance professionals, homeowners and home buyers understand the monetary impact of climate hazards on their real estate and investments — and you will help make that possible.

The successful candidate deeply cares about the environment, loves information technology, and appreciates the importance of data for the First Street mission. They will develop new peril models and enhance existing ones, lead data operations that span Climate Science, Data Science, and Data Engineering, and enable the broader team to succeed through your expertise and technical leadership.

Have you built machine learning models to calculate the impact of climate change on snow cover in Scandinavia? Have you reformatted terabytes of GRIB model output into a more accessible Zarr store? Do you use AI coding assistants to help write image processing algorithms for extracting building characteristics from satellite imagery? We’d love to hear from you!

What You'll Do:

• Lead acquisition, processing, and analysis of climate-related and geospatial data for First Street modelers and data partners.

• Develop and maintain scalable data pipelines on local and cloud-based systems (AWS preferred).

• Perform statistical analysis to validate hazard model predictions and assess model uncertainties.

• Develop and enhance machine learning models supporting First Street's peril product suite.

• Plan, execute, and direct Unix-based workflows using Python, Bash, GDAL, and related technologies.

• Analyze raster and vector data at scale to improve model accuracy, identify quality control issues, and develop remedies.

• Design and implement quality assurance checks on climate model data and derived statistics.

• Contribute to the broader Data Science and Data Engineering team's success through technical leadership and mentorship.

Requirements:

• Master's Degree + 4 years of experience, or Ph.D. + 2 years of experience (field: Data Science, Earth Science, or related)

• Python — required

• Linux & Bash — required

• Git & source control — required

• Cloud computing — required (AWS strongly preferred)

• Geospatial data and formats: GeoTIFF, NetCDF, GRIB, HDF5, Zarr

• Strong understanding of probability and statistics as applied to spatial data

• Experience with big data analysis, parallel pr