Lead Data Scientist IV - GEOINT/Remote Sensing

Pacific Northwest National Laboratory•Richland, WA

92d•Onsite

About The Position

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, Integrated Discovery 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 the National Security Directorate, combines profound domain expertise and creative integration of advanced hardware and software to deliver computational solutions that address complex data and analytic challenges. Working in multidisciplinary teams, we connect foundational research to engineering to operations, providing the tools to innovate quickly and field results faster. Our strengths are integrated across the data analytics lifecycle, from data acquisition and management to analysis and decision support. 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. 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.

Requirements

BS/BA and 7+ years of relevant work experience -OR- MS/MA and 5+ years of relevant work experience -OR- PhD with 3+ year of relevant experience
U.S. Citizenship
Ability to obtain and maintain a federal security clearance.
Must meet eligibility requirements for access to classified matter in accordance with 10 CFR 710, Appendix B.
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).
Must pass a drug test prior to commencing employment.
Must obtain and maintain a HSPD-12 Personal Identify Verification (PIV) Credential.
Must successfully complete the applicable tier of federal background investigation post hire and receive a favorable federal adjudication.
Must disclose any affiliation with the government of a country DOE has identified as a “country of risk” and recuse yourself of that affiliation or receive approval from DOE and Battelle prior to your first day of employment.

Nice To Haves

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 multi-disciplinary teams.

Responsibilities

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 serve as a role model for adhering to these standards.