Data Scientist (Virginia)

Kestrel Intelligence; Virginia (MN); Hybrid; USD 150,000 - 190,000; Full time

Benefits offered by this job

Based in CO Springs or DC areas

TS/SCI clearance preferred

Job summary

Kestrel Intelligence is seeking a Data Scientist to architect and deploy production-grade geospatial AI subsystems powering national security and commercial missions. You will build high-fidelity data pipelines, develop traditional ML models, and wrap them into tools for agentic AI, with emphasis on geospatial foundations and scalable architectures.

The role demands breadth across GDAL/SNAP stack and experience in multiple Geo domains, plus US citizenship. Remote-ready with security posture.

Qualifications

• Proven experience building geospatial data preprocessing pipelines (raster and vector) using the modern geospatial stack.
• Production-grade experience in at least two of the listed domains.
• Must be a US Citizen.

Responsibilities

• Architect end-to-end production-ready AI/ML and agentic subsystems for geospatial products.
• Build robust preprocessing pipelines for raster and vector data and integrate GeoFMs.
• Advance autonomous routing and operational geospatial capabilities for customers.

Skills

Geospatial Foundation Models

GeoAI/ML

SAR & Interferometry

Hyperspectral Imaging

RF Propagation

Digital Elevation Models

Autonomous Systems

Optimization

Economics

Tools

GDAL

SNAP

Rasterio

PostGIS

Job description

The Mission

At Kestrel, we are building the future of scalable autonomy across domains. Our systems enable commercial and national security customers to sense and act in support of complex missions without significant autonomous system expertise. This technology bridges domains (e.g., space, air, land, sea) and fields (e.g., AI, orbital dynamics, geospatial), requiring a team that has both breadth and depth in these related topics.

The Role

We are looking for an individual contributor to architect and deploy production-grade subsystems that power our cutting-edge products for both commercial clients and critical national security missions. As a Kestrel Data Scientist, you will lead the development of high-fidelity data processing pipelines, traditional AI/ML models, and wrapping them into tools for next-generation Agentic AI. You will work at the bleeding edge of geospatial science. This role requires adaptability, engineering rigor, and a deep respect for the mission.

Core Responsibilities:

• Architecture: Lead the end-to-end creation of production-ready AI/ML and agentic subsystems.
• Geospatial Engineering: Build robust preprocessing pipelines for raster and vector data (using GDAL, SNAP, rasterio, PostGIS).
• Innovation: Integrate emerging technologies, from Geospatial Foundation Models (GeoFMs) to autonomous route planning, into a cohesive operational picture.

You Must Be:

A master of foundational geospatial: Proven experience building geospatial data preprocessing pipelines (raster and vector) using the modern geospatial stack (GDAL, SNAP, rasterio, PostGIS, etc.).

A specialist: You must have production-grade experience in at least two (2) of the following domains:

• Traditional GeoAI/ML: Object detection/land classification (scikit, OpenCV, etc.).
• Geospatial Foundation Models: Utilizing GeoFMs like AlphaEarth, Prithvi, or Clay.
• SAR & Interferometry: Pipeline development (e.g., isce2).
• Hyperspectral Imaging: Processing (e.g., SPy).
• RF Propagation: Modeling signal data (e.g., CloudRF).
• Digital Elevation Models: Handling DEM in multiple formats (e.g., DTED).
• Autonomous Systems: Route planning for unmanned systems (e.g., Auterion, ArduPilot).
• Optimization: Complex scheduling for satellite constellations or aircraft.
• Economics: Models for resource allocation such as auction, bidding, pricing, waiting.

Must be a US Citizen

Bonus:

• Based in the Colorado Springs, CO or Washington, DC (working in customer sites in Crystal City, VA and Herndon, VA) areas
• Active Top Secret // Specially Compartmented Information (TS//SCI) clearance with counterintelligence-scope polygraph (CSP) or full-scope polygraph (FSP)