Hiring Event – Chief Data Scientist V

Pacific Northwest National Laboratory•Richland, WA

1d•Onsite

About The Position

The National Security Directorate (NSD) at PNNL drives science-based, mission-focused solutions to address complex, real-world threats. The AI and Data Analytics Division within NSD combines domain expertise with advanced hardware and software to deliver computational solutions for complex data and analytic challenges. This division works in multidisciplinary teams, connecting foundational research to engineering and operations, providing tools to innovate quickly and field results faster. Their strengths span the entire data analytics lifecycle, from acquisition and management to analysis and decision support. This role is part of a hiring event taking place during the weeks of October 12th to November 13th, with selected candidates invited for virtual and onsite interviews. The position is performed full-time onsite at the PNNL campus in Richland, WA or Seattle, WA.

Requirements

BS/BA and 9+ years of data science experience -OR- MS/MA and 7+ years of data science experience -OR- PhD with 5+ 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 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 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

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.
Relevant expertise includes 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.
Shape the technical direction of T&E for large-scale programs and conduct deep-learning research to investigate how models represent information, characterize how they behave, and develop methods to improve reliability.