Senior Data Scientist - Climate Risk

May 8

UrbanFootprint

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We develop the world’s first urban intelligence platform, enabling those who build our world to design a better future

Urban Planning • Spatial Data Analytics • Water Use Analytics • Energy Use Analytics • Greenhouse Gas Emissions Analytics

51 - 200

Description

• 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.

Requirements

• 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. • 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.

Benefits

• 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.)