North Point Technology is hiring a Data Scientist SME to own, harden, and scale GEOINT AI/ML pipelines for NGA’s Chinook modernization. You’ll lead advanced modeling on multi-source imagery and sensor data, operationalize models in the cloud, and deliver mission-grade analytics that accelerate analysts and decision-makers.
Locations: Gaithersburg, MD (primary); Alexandria, VA; Chantilly, VA; Aurora, CO; St. Louis, MO
Clearance: Top Secret with ability to obtain SCI and Polygraph
Responsibilities
-
Serve as technical SME for data science and geospatial analytics on high-impact GEOINT problems.
-
Design, develop, and validate ML/AI models for large, multi-source geospatial datasets (imagery, sensors, vector/raster).
-
Apply GEOINT/remote-sensing tradecraft to deliver scalable, mission-aligned analytics and decision support.
-
Recommend and integrate emerging tech (ML/AI, cloud, distributed compute) to improve workflows and outcomes.
-
Mentor and upskill data scientists/analysts on best practices and mission-relevant techniques.
-
Partner with GEOINT analysts, PMs, and engineers to shape requirements and technical approaches.
-
Conduct applied research in deep learning/reinforcement learning/advanced geospatial algorithms; transition to ops.
-
Deploy and monitor production models; ensure reliability, scalability, and actionable outputs.
-
Maintain thorough documentation of models, methods, and processes for reproducibility and knowledge transfer.
Basic Qualifications
-
U.S. citizenship (per contract).
-
Bachelor’s in Data Science, CS, Geospatial Science, or related field with 12–15 years’ relevant experience; or Master’s with 10–13 years; Doctorate welcome.
-
10+ years professional data science experience, including 5+ years with GEOINT/geospatial analysis.
-
Proven track record building and deploying ML/AI models for geospatial/remote-sensing use cases.
-
Deep knowledge of geospatial tools and tradecraft (GIS/ArcGIS), remote sensing, and IC applications.
-
Expert Python and DS libraries (TensorFlow or PyTorch, Pandas, NumPy); strong big-data experience (Spark/Hadoop; AWS or Azure).
-
Proficient with geospatial formats and libs (GeoTIFF, Shapefile, WMS/WFS; GeoPandas, Rasterio, GDAL).
-
Advanced experience operationalizing AI/ML for GEOINT (e.g., object detection on satellite imagery, spatial clustering, predictive analytics).
-
Strong visualization/reporting (Tableau, Power BI).
-
Excellent leadership, communication, collaboration, and problem-solving skills.
Preferred Qualifications
-
Advanced DS/ML certifications.
-
Familiarity with the Customer’s mission and GEOINT challenges.
-
Expertise in deep learning for computer vision/image analysis in geospatial contexts.
-
Experience with cloud-native/distributed architectures for geospatial workloads.
-
Familiarity with satellite data analysis and remote-sensing models.
-
Publications in GEOINT, ML, or data science.
