Geospatial Data Scientist Lead

Neural Earth

2d • $185,000 - $231,000

About The Position

We are NEURAL EARTH. We bring clarity to physical risk, enabling leaders to engage with confidence and enact resilient, business-critical decisions. Today's environmental, economic, and infrastructure challenges are deeply interconnected, yet the data required to understand these relationships is scattered across siloed and aging systems. Neural Earth enables operational execution, delivering a single decision intelligence platform that unifies planetary, governmental, and asset-level data, always on and always learning. This is technical work that requires patience. It requires teams willing to operate at the intersection of AI research, geospatial science, distributed systems, and enterprise deployment. It is also incredibly rewarding. Join us at Neural Earth — the next frontier is here.

Neural Earth's Science team transforms raw environmental data into intelligence that moves markets and protects lives. You will join a growing group of geospatial data scientists, ML specialists, and researchers led by a strong leader, who sets a high bar: the work must be publishable in quality and deployable in production. You will collaborate closely with Engineering, Product, and Revenue to make sure what we build in science reaches the customers who need it.

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!

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

Nice To Haves

• 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.

Responsibilities

• 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.
• 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.
• Convert complex, multi-hazard scientific findings into business-ready products that are legible and compelling to insurance underwriters, government operators, and enterprise decision-makers.
• 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.
• Establish rigorous validation standards for all geospatial models, ensuring methods are reproducible, cross-validated, and defensible across industries and geographies.

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

What This Job Offers

• Job Type: Full-time
• Career Level: Senior