Geospatial Data Science Lead: Hazard Pipelines & Insight

Neural Earth, Inc.; United States; Sur place; USD 185 000 - 231 000; Plein temps

Avantages offerts par ce poste

Health, dental, and vision insurance

Bonuses

Paid time off

Life insurance

HSA/FSA options

Résumé du poste

Neural Earth, Inc. is seeking a staff-level leader to own the geospatial data science function.

You will define technical strategy for ingesting, structuring, and piping multi-hazard geospatial data to power hazard intelligence products for insurers, government agencies, and infrastructure operators. You will build and scale production pipelines, enable ML/AI teams, and ensure data is understandable to non-scientists.

Qualifications

• 5+ years of experience with geospatial data in a research or applied setting
• Prior experience in insurance, energy, government, defense, or climate tech
• Demonstrated ability to build and lead a technical capability, including mentoring or managing at least one direct report

Responsabilités

• Design and deploy Python-based geospatial models that quantify hazards for business decisions
• Architect geospatial data pipelines from the ground up, including systems and frameworks to feed ML/AI models
• Translate complex multi-hazard findings into business-ready products for underwriters and enterprise decision-makers
• Lead internal and external geospatial data science work, guiding customer calls and proposals while developing a direct report
• Establish rigorous validation standards for geospatial models ensuring reproducibility and cross-geo defensibility

Connaissances

Python programming

Geospatial data

Data pipelines

Formation

Master's or PhD in Geospatial Science

Outils

GeoPandas

Rasterio

GDAL

xarray

Shapely

Description du poste

Neural Earth, Inc. is seeking a staff-level leader to own the geospatial data science function.

You will define technical strategy for ingesting, structuring, and piping multi-hazard geospatial data to power hazard intelligence products for insurers, government agencies, and infrastructure operators. You will build and scale production pipelines, enable ML/AI teams, and ensure data is understandable to non-scientists.