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Taking the next step in your career with UrbanFootprint will set you on the path to revolutionizing how organizations make decisions.
UrbanFootprint is the world’s first Urban Intelligence Platform – trusted by some of the largest energy utilities, financial institutions, government agencies, urban planning firms, and mobility companies in the US to provide geospatial insights and find signal through noise to inform site selection, infrastructure investment, resource distribution, and much more. We do this by unifying and normalizing previously siloed data on climate, environmental, urban, and socio-economic factors to surface powerful and actionable data insights.
UrbanFootprint’s mission is to Build Resilience by empowering organizations with critical data insights to drive decision making and allow them to Never Wonder Where. Our customers answer complex ‘where’ questions in minutes versus weeks, months, or years, such as:
- ”Where does the energy sector need to invest in electrification, decarbonization, and asset hardening in the face of climate threats?”…
- ”Where should cities and businesses invest to catch up with e-commerce, last-mile delivery, and new mobility?”…
- ”Where do governments deploy relief and new infrastructure to combat record hunger, homelessness, and hazard vulnerability?”…
Led by our co-founders, Joe DiStefano and Peter Calthorpe, we are tackling a $22B market opportunity. We’ve won awards including Inc. Magazine’s Best in Business and have been named one of Fast Company’s World’s Most Innovative Companies. We raised a $25M Series B and our investors include Social Capital, Citi Ventures, Valo Ventures, 2150.VC, A/O Proptech, Assured Guaranty, and Radicle Impact.
Don’t wonder where to go next, we’ve got the perfect spot for you!
The role
As a Senior Data Scientist focused on Climate Risk, you will contribute to the evolution of UrbanFootprint’s climate and hazard risk-based data products, including Physical Climate Risk, Grid Resilience Insights, and Municipal Bonds Insights. These products are designed to help asset managers and financial institutions make investment decisions by taking into account climate hazard risk, community impacts and vulnerability, and physical infrastructure and the built environment. These data products leverage our parcel-level map of all properties across the US to facilitate decision-making for scales ranging from parcels and neighborhoods to states and the entire US.
As a product-minded and pragmatic data scientist, you know how to appropriately scope projects to ensure we deliver what customers need today and have ideas for improving in the future. You are autonomous, not independent; you work collaboratively with business partners to understand the ‘what’ and ‘why’ and take full ownership of figuring out the ‘how’ to meet those needs. You proactively communicate progress and are accountable for the validity, accuracy, and applicability of all the models you build. You take pride in the models you build and recognize that solutions don’t need to be perfect to make a difference in the world.
What you’ll do:
- Propose and develop novel models and algorithms to quantify climate impact that reflect risks to business and society.
- Own data science problems end-to-end, from ideation, exploratory data analysis, and prototype to collaborating with data engineers to ship models to production.
- Identify, normalize, and analyze various historical weather and climate datasets to assess where risks are the highest.
- Help to define and communicate a quantified understanding of risk across multiple products.
- Communicate technical information, such as model methodology, accuracy, and weaknesses, to non-technical partners regarding product, sales, and customer success.
Your background most likely includes:
- Work experience equivalent to a Master’s degree or higher in Earth system sciences (Earth, Atmospheric, Oceanic, or Geo Sciences), Hazard, Disaster, or Catastrophe Science, Statistics or Computer Science (with an emphasis on weather or climate modeling), or similar technical fields with an emphasis on geospatial, spatiotemporal or machine learning modeling.
- Experience working with publicly available climate and historical weather data, including CMIP6 and downscaled CMIP6 datasets (e.g., LOCA), reanalysis data (e.g., MERRA, ERA-5, NARR), and others.
- Practical experience with various statistical and machine learning models applied to climate and weather modeling, such as climate model downscaling, prediction of extreme events, or flooding modeling.
- Experience estimating risk or quantifying the impact of climate or weather-related events (e.g., damage estimates, rebuilding costs, population impacts, or economic losses).
- Fluency in Python and Python’s scientific programming stack, such as pandas, GeoPandas, rasterio, pangeo, sklearn, pytorch, fastai, statsmodels, and various visualization packages, including map-based visualizations.
- Experience developing models in an iterative, fast-paced environment.
- Excellent communication, collaboration, and documentation skills.
Bonus qualifications:
- Experience with Catastrophe modeling or process-based models of flood, wildfire, or hurricanes.
- Experience working with satellite data such as LandSat or MODIS.
- Experience developing and scaling models in a cloud environment (GCP preferred).
- Deep experience with geospatial modeling and analysis, including familiarity with raster rescaling, joining rasters to vector features, and spatiotemporal modeling.
- Experience as a full-stack data scientist, owning data pipelines, model development, and production model implementation.
- Expertise in large-scale data analysis frameworks, including SQL/PostgreSQL, Apache Beam, Dask or PySpark.
- Passion for climate resilience, equity, urban planning, and leveraging data to facilitate a more equitable and resilient society.
Target salary: $130,000 - $200,000, plus bonus eligibility and equity.
(Compensation is flexible based on experience; all candidates at various levels will be considered.)
UrbanFootprint is committed to diversity in its workforce. We are committed to equal employment opportunity regardless of race, color, religion, creed, gender, national origin, age, disability, veteran status, marital status, pregnancy, sex, gender expression or identity, sexual orientation, citizenship, or any other legally protected class.
