Develop orbit determination and propagation applications for the Spacecraft Control Subsystem, improving accuracy, efficiency, and reliability for StriX satellite operations.
About this role
Within Synspective’s Solution Development Department, the Geospatial Applied Scientist helps build an analytics platform that produces geoscience insights from multiple sources, including satellite imagery. The role organizes needs from internal teams, partners, and customers and communicates results with scientists and business stakeholders.
The scientist researches algorithms and writes code to extract insights from SAR imagery, selecting approaches through literature review and trials. Work combines SAR with optical satellite data, infrastructure polygons, and weather data, using image processing, statistical learning, and deep learning. The posting names Python, NumPy/Pandas, scikit-learn, SciPy, GDAL, rasterio, GeoPandas, Shapely, and Git.
Applicants must have a bachelor’s degree in data science, statistics, computer science, or a related field; production-ready Python proficiency; familiarity with raster and vector formats; hands-on GDAL and Python geospatial-library experience; and experience building analytics with geospatial data.
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