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Geospatial Data Scientist

🌐 Remote💼 Full-time🗓 2026-09-23 → 2026-09-26

Core

Develop geospatial and remote-sensing methods to turn satellite imagery and spatial data into reliable analytical products for defense, law enforcement, and enterprise teams.

Role type

Senior IC Geospatial Data Scientist (Remote Sensing)

Builds

Geospatial data services, remote-sensing capabilities, and a web-based common operational picture for the Sentinel platform.

Domain

Defense, Law Enforcement, Enterprise; Remote Sensing, Earth Observation, Geospatial Intelligence

Deliverable

production ML models

Required skills

Python, scientific computing (NumPy, pandas, SciPy, xarray, GeoPandas, Rasterio/GDAL), machine learning (scikit-learn, PyTorch), deep learning (Vision Transformers, U-Nets), remote-sensing fundamentals (spatial/spectral/radiometric/temporal resolution, coordinate systems), satellite image analysis (change detection, segmentation, object detection, classification), statistical judgment (sampling, spatial autocorrelation, data leakage, uncertainty), reproducible engineering practices.

Preferred skills

thermal infrared imagery processing, SAR data analysis, geospatial foundation models (Prithvi, TerraMind, AlphaEarth), large-scale geospatial analysis (Dask, Apache Spark/Sedona, Zarr), GPU inference optimization (PyTorch/CUDA, ONNX Runtime, TensorRT, NVIDIA Triton), Spatial SQL (DuckDB, PostGIS), STAC, QGIS, geemap, COG, GeoParquet, commercial imagery providers (Airbus, Satellogic, SatVu, ICEYE), defense/intelligence environment experience, agentic software development.

Technologies

Python, NumPy, pandas, SciPy, xarray, GeoPandas, Rasterio, GDAL, scikit-learn, PyTorch, TorchGeo, Vision Transformers, U-Nets, Dask, Apache Spark, Sedona, Zarr, DuckDB, PostGIS, STAC, QGIS, geemap, ONNX Runtime, TensorRT, NVIDIA Triton Inference Server

Responsibilities

Develop change-detection workflows for satellite time series; build and evaluate object-detection, segmentation, and classification methods for satellite imagery; assess sensor suitability and design preprocessing/feature extraction pipelines; combine raster outputs with vector/temporal data for spatial statistics and anomaly detection; build reference datasets and evaluation protocols; package tested Python methods for batch processing or inference; integrate methods into Sentinel workflows with data and platform engineers.

Seniority

Senior, hands-on IC

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