Lead Data Scientist IV - GEOINT​/Remote Sensing

Overview

PNNL’s AI and Data Analytics Division within the National Security Directorate seeks a Lead Data Scientist to develop geospatial intelligence (GEOINT) solutions that address critical national security challenges. The role involves interdisciplinary research, machine‑learning model development, and deployment of data‑driven solutions within operational environments.

• Designs and implements innovative GEOINT data science solutions, addressing complex technical challenges related to imagery analysis, object detection, data fusion, and geospatial workflows.
• Serves as a principal investigator (PI) or co‑PI on projects or tasks contributing to the integration of multiple capabilities or interdisciplinary approaches.
• Leads efforts to develop and deploy ML pipelines to process and analyze large quantities of geospatial data in operational environments.
• Mentors and guides junior staff, fostering technical excellence and professional development within the team.
• Explores and generates new ideas for proposals and business opportunities by identifying emerging national security needs related to GEOINT analytics.
• Builds and maintains external partnerships to increase the technical reputation of the team and align project outcomes with sponsor priorities.
• Collaborates with multi‑disciplinary teams, including software engineers, geospatial analysts, and operational mission specialists, to transition research outputs into usable, field‑ready solutions.
• Ensures compliance with quality, safety, and security standards in all project tasks and serves as a role model for adhering to these standards.

• BS/BA and 7+ years of relevant work experience, OR MS/MA and 5+ years of relevant work experience, OR PhD with 3+ years of relevant experience.

• Advanced degree in data science, computer science, physics, mathematics, or a similar discipline.
• Expertise in GEOINT workflows, including experience with remote sensing platforms, multi‑modal data fusion, and advanced geospatial analytics.
• Experience working with hyperspectral imaging data in the long‑wave infrared, including developing and validating machine‑learning–based detection, classification, and unmixing algorithms; full product pipeline experience (radiometric calibration, atmospheric correction, geometric correction, etc.); strong spectral sensing fundamentals (radiative transfer, reflectance/emissivity, absorption features, SNR/noise modeling, sensor characterization); applying ML techniques to hyperspectral data fusion for geospatial intelligence applications; proficiency with hyperspectral analysis and visualization tools (e.g., ENVI/IDL).
• Experience working with Synthetic Aperture Radar (SAR) data (complex/IQ and formed products), including developing and validating both traditional signal‑processing and machine‑learning–based detection and classification algorithms; end‑to‑end SAR image product conversion pipeline experience; proficiency with SAR rendering tools; strong knowledge of SAR/RADAR theory fundamentals (wave propagation, scattering, speckle, Doppler/geometry, calibration, etc.).
• Hands‑on experience and strong proficiency with geospatial analysis tools (e.g., GDAL, Geo Pandas, Google Earth Engine) and machine learning frameworks (e.g., Tensor Flow, PyTorch).
• Experience training, fine‑tuning, and applying deep learning models for remote sensing and GEOINT applications, including Automatic Target Recognition (ATR), object detection, and segmentation, using models and frameworks such as YOLO, Detectron2, DINOv2, Segment Anything Model (SAM), Vision Transformers, and geospatial foundation models.
• Experience deploying operational solutions, ensuring scalability and applicability in secure or mission‑critical environments.
• Proven success in proposal development and securing external funding to support technical work or research programs.
• Experience working with or supporting national security mission sponsors such as the Department of Energy (DOE), Department of Defense (DoD), Department of Homeland Security (DHS), or similar organizations.
• Strong communication and leadership skills, including the…