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Geospatial Data Scientist Lead

neural-earthUnited StatesProduct Engineering
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Salary
$185K to $231K
Job type
Full-time
Work mode
Remote
Experience
Lead · 5+ yrs
Posted
6 Oct 2026
Status
Open · checked 7d ago

About this role

This founding, staff-level Geospatial Data Scientist Lead role is located in the United States and suits an experienced professional who bridges geospatial engineering, data infrastructure, and applied science to build production-grade hazard intelligence systems. The position sits within the Science team at Neural Earth, where the focus is on delivering a single decision intelligence platform that unifies planetary, governmental, and asset-level data.

Role Overview

The Geospatial Data Scientist Lead owns the geospatial data science function at Neural Earth. This position defines the technical strategy for ingesting, structuring, and pipelining multi-hazard geospatial data to power quantified intelligence products for insurers, government agencies, and infrastructure operators. The role operates at the intersection of AI research, geospatial science, distributed systems, and enterprise deployment, managing a direct report and serving as an internal and external subject matter expert.

Key Responsibilities

Design and deploy Python-based geospatial models that quantify environmental and physical hazards to drive business decisions.
Architect geospatial data pipelines from the ground up, structuring and preparing data for machine learning and artificial intelligence teams.
Convert complex scientific findings into business-ready products legible to insurance underwriters, government operators, and enterprise decision-makers.
Serve as the subject matter expert on geospatial data science by leading customer calls, proposals, and strategy discussions while managing a direct report.
Establish rigorous validation standards for all geospatial models to ensure reproducible, cross-validated, and defensible methods across industries and geographies.

Requirements

Master's or PhD in Geospatial Science, Data Science, Atmospheric or Environmental Science, or a related field.
Minimum of 5 years of experience with geospatial data in a research or applied setting, outside of academic training.
Prior experience working 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.

Skills and Tools

Python
GeoPandas
Rasterio
GDAL
xarray
Shapely
GeoTIFF, COG, GeoParquet, and NetCDF data formats
Cloud environments

Salary and Benefits

Annual salary range between $185,000 and $231,000.
Company performance-based cash bonuses.
Majority employer-paid health, dental, and vision insurance for employees and dependents.
Flexible Paid Time Off.
Group Life Insurance at two times the base salary, paid by the company.
Flexible Spending Account and Health Savings Account options.

About the Company

Neural Earth brings clarity to physical risk by delivering a decision intelligence platform that unifies planetary, governmental, and asset-level data. The company operates at the intersection of AI research, geospatial science, distributed systems, and enterprise deployment to help leaders enact resilient, business-critical decisions.

How to Apply

Apply on the official company careers page.

Skills and tech stack

PythonGeoPandasRasterioGDALxarrayShapelyGeoTIFFCOGGeoParquetNetCDFDistributed Systems

Questions candidates ask

What is the salary range for the Geospatial Data Scientist Lead role?

The annual salary range is $185,000 to $231,000.

What education is required for this position?

A Master's or PhD in Geospatial Science, Data Science, Atmospheric or Environmental Science, or a related field is required.

How many years of experience are needed?

Candidates must have 5+ years of experience with geospatial data in a research or applied setting, outside of academic training.

What location is specified for the job?

The job location is the United States.

What specific Python libraries are mentioned for building models?

GeoPandas, Rasterio, GDAL, xarray, and Shapely.

Ready to apply?

The application is on the official neural-earth careers page.

Apply on company site