Geospatial Data Scientist

Role Description

This is a founding, staff-level role with a direct report. You will own Neural Earth's geospatial data science function, define the technical strategy for how we ingest, structure, and pipeline multi-hazard geospatial data, and make that data usable by our ML and AI teams to power quantified intelligence products used by insurers, government agencies, and infrastructure operators. You are comfortable across geospatial data broadly, not specialized in a single sub-discipline like meteorology. You work at the intersection of geospatial engineering, data infrastructure, and applied science. You do not stop at the paper. You build things that ship, scale, and make hazard data understandable to people who are not scientists. This is you!

How You'll Be Successful

• Model: Design and deploy Python-based geospatial models that quantify environmental and physical hazards at a level of precision that drives real business decisions, not just research outputs.
• Build: Architect Neural Earth's geospatial data pipelines from the ground up, including the systems, infrastructure, and scientific frameworks that turn raw hazard data into indexed intelligence products customers can act on. Structure and prepare that data so it is ready to run through the models our ML and AI teams build, and own the production pipelines that keep it flowing reliably.
• Translate: Convert complex, multi-hazard scientific findings into business-ready products that are legible and compelling to insurance underwriters, government operators, and enterprise decision-makers.
• Lead: Serve as Neural Earth's internal and external subject matter expert on geospatial data science, driving customer calls, proposals, and strategy discussions, while managing and developing a direct report.
• Validate: Establish rigorous validation standards for all geospatial models, ensuring methods are reproducible, cross-validated, and defensible across industries and geographies.

Qualifications

• You have 5+ years of experience working with geospatial data broadly, across formats and hazard types, in a research or applied setting, in addition to any graduate degree.
• You write Python fluently and have built production-grade geospatial models using GeoPandas, Rasterio, GDAL, xarray, and Shapely.
• You know how to engineer and structure geospatial data so it is ready to feed ML and AI models built by others. You would rather apply and extend someone else's research five different ways than chase original research yourself.
• You are fluent in geospatial data formats (GeoTIFF, COG, GeoParquet, NetCDF) and have worked with large-scale raster, vector, and time-series datasets in cloud environments.
• You have shaped a scientific or technical framework, not just executed within someone else's.
• You think in systems. When you see a wildfire burn scar, your mind goes to downstream snowpack risk.
• You can walk a customer through a confidence interval in the morning and brief a C-suite on business implications in the afternoon, without ever sounding condescending or over your audience's head.
• You define your own structure in ambiguous environments and build something real before the roadmap is written.
• You do not ship unvalidated models. You have the judgment to know when something is ready.
• You have mentored or managed at least one direct report or informally led technical work, and you know how to grow talent, not just do the work yourself.
• You care when your hazard model shapes an insurance decision or informs a disaster response. This matters to you.

Requirements

• Master's or PhD in Geospatial Science, Data Science, Atmospheric or Environmental Science, or a related field.
• 5+ years of experience with geospatial data in a research or applied setting, outside of academic training.
• Prior experience in insurance, energy, government, defense, or climate tech.
• Demonstrated ability to build and lead a technical capability, including managing or mentoring at least one direct report.

Benefits

• Competitive base compensation regardless of work location.
• Company performance-based cash bonuses.
• Majority employer-paid health, dental, and vision insurance for you and your dependents.
• Flexible Paid Time Off (PTO).
• Group Life Insurance at 2x your base salary, paid by the company.
• FSA and HSA options to maximize your healthcare dollars.