Lead Data Scientist IV - GEOINT/Remote Sensing
Pacific Northwest National Laboratory
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Benefits offered by this job
Job summary
Pacific Northwest National Laboratory (PNNL) seeks an experienced Lead Data Scientist to advance GEOINT data science initiatives. You will develop ML models, analyze geospatial data, and collaborate with interdisciplinary teams to deliver field-ready solutions for national security challenges.
The role emphasizes leadership, cutting-edge analytics, and the translation of research into practical tools, with emphasis on scalable, secure deployments and cross‑functional collaboration.
Qualifications
- BS/BA with 7+ years of relevant experience or MS/MA with 5+ years or PhD with 3+ years
- Security clearance eligibility required for federal program participation
- Strong background in geospatial analytics and ML for GEOINT applications
Responsibilities
- Designs and implements GEOINT data science solutions for imagery analysis and geospatial workflows.
- Leads ML pipelines to process large geospatial datasets in operational environments.
- Mentors junior staff and fosters technical excellence within the team.
- Collaborates with engineers and analysts to transition research into field-ready solutions.
Skills
Education
Tools
Job description
At PNNL, our core capabilities are divided among major departments that we refer to as Directorates within the Lab, focused on a specific area of scientific research or other function, with its own leadership team and dedicated budget. Our Science & Technology directorates include National Security, Earth and Biological Sciences, Physical and Computational Sciences, and Energy and Environment. In addition, we have an Environmental Molecular Sciences Laboratory, a Department of Energy, Office of Science user facility housed on the PNNL campus. The National Security Directorate (NSD) drives science‑based, mission‑focused solutions to take on complex, real‑world threats to our nation and the world. The AI and Data Analytics Division, part of NSD, combines profound domain expertise and creative integration of advanced hardware and software to deliver computational solutions that address complex data and analytic challenges.
PNNL is seeking a Lead Data Scientist with expertise 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, develop machine‑learning (ML) models, analyze geospatial datasets, and perform research that bridges cutting‑edge methods and field‑ready solutions.
- 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 multidisciplinary 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.
Minimum Qualifications:
- 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, GeoPandas, Google Earth Engine) and machine learning frameworks (e.g., TensorFlow, 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 ability to present technical findings to diverse audiences and stakeholders and to collaborate effectively within multidisciplinary teams.
Not applicable.
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. 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).
Our laboratory is committed to fostering a work environment where all individuals are treated with fairness and respect while solving critical challenges in fundamental sciences, national security, and energy resiliency. We are an Equal Employment Opportunity employer. Pacific Northwest National Laboratory (PNNL) is an Equal Opportunity Employer. PNNL considers all applicants for employment without regard to race, religion, color, sex, national origin, age, disability, genetic information (including family medical history), protected veteran status, and any other status or characteristic protected by federal, state, and/or local laws. We are committed to providing reasonable accommodations for individuals with disabilities and disabled veterans in our job application procedures and in employment. If you need assistance or an accommodation due to a disability, contact us at careers@pnnl.gov.
- Medical, dental, and vision insurance; telehealth options; mental health benefits; wellness coaching; health savings account; flexible spending accounts; basic life insurance; disability insurance; employee assistance program; business travel insurance; tuition assistance; relocation; backup childcare; legal benefits; supplemental parental bonding leave; surrogacy and adoption assistance; fertility support.
- Automatic enrollment in company‑funded pension plan; 401(k) savings plan with company match.
- Up to 120 vacation hours per year and ten paid holidays per year.
- All benefits are dependent upon eligibility and may vary for Research Associates.
PNNL lists the full pay range for the position in the job posting. Starting pay is calculated from the minimum of the pay range and actual placement in the range is determined based on an individual’s relevant job‑related skills, qualifications, and experience. This approach is applicable to all positions, with the exception of positions governed by collective bargaining agreements and certain limited‑term positions which have specific pay rules. As part of our commitment to fair compensation practices, we do not ask for or consider current or past salaries in making compensation offers at hire.
USD $166,800.00 per year.
USD $275,200.00 per year.
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