Data Scientist II - GEOINT/Remote Sensing

Data Scientist Pacific Northwest National Laboratory (PNNL) is seeking a Data Scientist with solid experience in data science and a passion for solving mission-critical challenges in the geospatial intelligence (GEOINT) domain. The selected candidate will contribute to research and development programs within the AI and Data Analytics Division which specializes in data science, applied mathematics, advanced analytic architectures, software engineering, and human-centered computing. The Data Scientist will work as part of interdisciplinary teams to deliver data-driven solutions that address critical national security challenges. This individual will collaborate with peers to develop machine learning (ML) models, analyze geospatial datasets, and perform research that bridges cutting-edge methods and field-ready solutions. The candidate will support PNNL's mission by contributing to impactful R&D projects that help tackle national challenges. Successful candidates will have the opportunity to grow professionally while working on diverse, mission-focused projects. At PNNL, we foster a collaborative and innovative work environment aimed at lifelong learning, creative problem-solving, and advancing interdisciplinary, data-driven innovation. This position is based in either Richland, WA or Seattle, WA and requires an onsite presence. Minimum Qualifications: BS/BA and 2 years of relevant experience -OR-

MS/MA -OR-

PhD Preferred Qualifications: Degree in data science, computer science, physics, mathematics, or similar discipline. Demonstrated experience in GEOINT workflows, including experience with remote sensing platforms, multi-modal data fusion, and advanced geospatial analytics. 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 with long-wave infrared (LWIR) hyperspectral imagery, Synthetic Aperture Radar (SAR), and/or electro-optical (EO) data. Hands-on experience with geospatial analysis tools (e.g., GDAL, GeoPandas, Google Earth Engine) and machine learning frameworks (e.g., TensorFlow, PyTorch). Demonstrated strong communication and collaboration skills, with the ability to present technical findings to diverse audiences and work effectively within multi-disciplinary teams. This position requires the ability to obtain and maintain a federal security clearance. A security clearance background investigation includes review of your employment, education, financial, and criminal history, as well as interviews with you and your personal references, neighbors, and co-workers to determine trustworthiness, reliability, and loyalty to the United States. The investigation also examines your foreign connections, drug and alcohol use, foreign influence, and overall conduct. Requirements: U.S. Citizenship Background Investigation: Applicants selected will be subject to a Federal background investigation and must meet eligibility requirements for access to classified matter in accordance with 10 CFR 710, Appendix B. Drug Testing: All Security Clearance positions are Testing Designated Positions, which means that the applicant selected for hire is subject to pre-employment drug testing, and post-employment random drug testing. In addition, applicants must be able to demonstrate non-use of illegal drugs, including marijuana, for the 12 consecutive months preceding completion of the requisite Questionnaire for National Security Positions (QNSP). Note: Applicants will be considered ineligible for security clearance processing by the U.S. Department of Energy if non-use of illegal drugs, including marijuana, for 12 months cannot be demonstrated. This position is a Testing Designated Position (TDP). The candidate selected for this position will be subject to pre-employment and random drug testing for illegal drugs, including marijuana, consistent with the Controlled Substances Act and the PNNL Workplace Substance Abuse Program. PNNL