Hiring Event – Lead Data Scientist IV

Pacific Northwest National Laboratory•Richland, WA

1d•Onsite

About The Position

The AI and Data Analytics Division, part of the National Security Directorate (NSD), at PNNL 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. This role is performed full-time onsite at the PNNL campus in Richland, WA or Seattle, WA. With new projects and expanding programs, our AI and Data Analytics Division offers opportunities to advance cutting-edge research and build solutions for critical national security missions. Join a team of more than 400 data scientists, software engineers, mathematicians, and human-centered computing researchers turning ambitious ideas into real-world capabilities. We’re looking for passionate Lead Data Scientists who are motivated to advance the state of the art in AI for national security missions.

Requirements

BS/BA and 7+ years of data science experience -OR- MS/MA and 5+ years of data science experience -OR- PhD with 3+ years of data science experience
Experience with Python and AI/ML frameworks.
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 successfully complete the applicable tier of federal background investigation post hire and receive a favorable federal adjudication.
Must not have any affiliation with the foreign government of a country DOE has identified as a “country of risk” without explicit approval by DOE and Battelle.

Nice To Haves

Strong scientific foundations and expertise in spectral sensing, radiometric and atmospheric correction, machine learning-based detection and classification, spectral unmixing, multimodal data fusion, sensor characterization, or related GEOINT workflows.
Relevant expertise includes training, alignment, parameter-efficient tuning, and augmenting LLMs/VLMs, or designing novel agentic architectures with advanced routing, retrieval, tool integration, and state-space representation.
Evaluation beyond aggregate metrics, probing model internals, explainable AI, adversarial ML (blue/red teaming), uncertainty quantification, mechanistic interpretability, robustness, and the scientific design of automated evaluation harnesses.

Responsibilities

Advance mission-focused applications of hyperspectral imaging, remote sensing, and geospatial intelligence.
Advance applied research in adapting and aligning foundation models, designing advanced reasoning architectures, and enhancing the performance, behavior, or capabilities of agentic frameworks.
Lead research efforts in defining, designing, and validating rigorous Test & Evaluation (T&E) methods to characterize the capabilities, limitations, and operational readiness of AI models and systems.