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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior Data Scientist III - Machine Learning for GEOINT and Remote Sensing - **Company:** Pacific Northwest National Laboratory - **Location:** Richland, WA, United States - **Experience:** Expert - **Salary:** $140,200 - **Contract:** Temporary contract - **Skills:** Training Data, Artificial Intelligence, Algorithm Design, Geospatial Intelligence, Intelligence Analysis, Machine Learning, Data Processing, Pytorch, Transfer Learning, Deep Learning, Agentic-AI, Few-Shot Learning, Low Latency, Data Analytics - **Published:** November 8, 2026 - **Apply:** https://www.nexxt.com/job.asp?id=3505225679&tx=KK4343FFL&pt=1&aff=0B19D771-A501-4A5E-8338-2A822B784D54&utm_source=Job%20Feed&utm_medium=textkernel&utm_campaign=DE&utm_term=0B19D771-A501-4A5E-8338-2A822B784D54 ## About the Role * BS/BA and 5+ years of data science experience -OR- * MS/MA and 3+ years of data science experience -OR- * PhD with 1+ year of data science experience * Experience applying and evaluating deep learning methods for detection and classification in electro-optical (EO) imagery or target detection and material classification in hyperspectral imagery (HSI). * Experience developing deep learning methods using PyTorch or another deep learning framework., * Experience with the EO or HSI imaging chain, including sensor response, image formation, calibration, and data processing. LWIR HSI experience is particularly valued. * Experience in addressing limited labeled training data or new target categories through methods such as few-shot learning, transfer learning, or open-vocabulary models. * Experience with multimodal or temporal fusion for geospatial analysis, or agentic workflows that coordinate models, geospatial tools, and data sources, including evaluation of workflow reliability and analytic results. * Experience translating research into methods or tools used in applied settings, or developing and evaluating models for edge or onboard platforms with size, weight, and power (SWaP) constraints, balancing accuracy, latency, memory, and energy use. * Experience supporting national security missions or developing proposals. Hazardous Working Conditions/Environment Not applicable. Additional Information 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., * 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. ## Description PNNL is seeking a Senior Data Scientist III with deep learning expertise to develop methods for detecting and classifying targets in electro-optical (EO) imagery or identifying targets and materials in hyperspectral imagery (HSI). This research supports geospatial intelligence (GEOINT) and national missions. In the AI and Data Analytics Division, you will lead research projects or major parts of larger projects, developing methods from initial ideas through evaluation and integration into research prototypes. Current priorities include automatic target recognition (ATR), long-wave infrared (LWIR) HSI target detection and material classification, and detection and classification with limited labeled training examples, particularly in EO imagery. The role also offers opportunities to explore related problems in remote sensing and intelligence analysis. Candidates with deep learning experience in EO, HSI, or related sensing applications are encouraged to apply. You will work alongside researchers and domain specialists on difficult national science and technology challenges. Collaboration with software and machine learning (ML) engineers will reflect each project's needs and stage of development. Opportunities to advance existing research and pursue new ideas may come through ongoing projects, internal research investments, or new proposals., * Develop and adapt detection and classification methods through algorithm development, mathematical analysis, experimentation, or implementation. * Lead research projects or major technical efforts, coordinate contributors, and plan the work, resources, and milestones. * Evaluate methods against appropriate baselines using representative data. Investigate classification errors, false alarms, robustness, and limitations that affect their use. * Build and validate research prototypes with software and ML engineers, addressing technical barriers to integration and deployment. * Work with collaborators to turn mission or user needs into research questions, and communicate findings through analyses, technical reports, and discussions. * Develop research ideas and collaborate with project leaders on proposals to support your research. * Mentor colleagues, help recruit and onboard researchers, and share methods and findings across disciplines. * Follow applicable quality, safety, and security requirements.