Senior Earth Data Scientist: Geospatial Insight Architect

Parallel Group; Seattle (WA); Hybrid; USD 140,000 - 190,000; Full time

Benefits offered by this job

Health insurance

Dental & Vision insurance

401(k) with company match

Paid vacation & holidays

Job summary

Earth Finance is seeking a Senior Earth Data Scientist to advance SpatiaFi and related products. You will own the science-to-insight pipeline, integrating multi-source earth observations into derivative financial insights for decision support.

You will lead production-ready models, work with GeoAI foundations, and ensure scalable cloud-based solutions across satellite rasters, reanalysis grids, and climate projections.

Qualifications

• Earth/atmospheric scientist with 5+ years in applied science and data modeling.
• Translate peer‑reviewed formulas into production‑ready Python code for geospatial indices.
• Harmonize raster, reanalysis, and multi‑decadal projection data into unified analytical layers.
• Expertise in PyData stack: pandas, geopandas, xarray, dask, scikit‑learn.
• Cloud‑native geospatial experience with GEE, Vertex AI or similar platforms.

Responsibilities

• Lead development of derivative geospatial insights and models.
• Architect production-ready models translating scientific formulas into indices.
• Leverage cloud tooling and robust Python development practices.
• Deploy and fine‑tune GeoAI models for multi‑layer spatial reasoning.
• Collaborate with Spatial Finance analysts and tech teams to productionize models.

Skills

Earth Science

Python (PyData)

Geospatial analysis

Google Earth Engine

Cloud-native GIS

Machine learning

Education

Earth/Atmospheric science

Tools

Pandas

Geopandas

Xarray

Dask

Scikit-learn

QGIS

Job description

Earth Finance is seeking a Senior Earth Data Scientist to advance SpatiaFi and related products. You will own the science-to-insight pipeline, integrating multi-source earth observations into derivative financial insights for decision support.

You will lead production-ready models, work with GeoAI foundations, and ensure scalable cloud-based solutions across satellite rasters, reanalysis grids, and climate projections.