Hiring Event – Senior Data Scientist III

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 to provide tools for rapid innovation and faster results. Their strengths span the entire data analytics lifecycle, from acquisition and management to analysis and decision support. This role offers opportunities to advance cutting-edge research and build solutions for critical national security missions, joining a team of over 400 data scientists, software engineers, mathematicians, and human-centered computing researchers.

Requirements

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 with Python and AI/ML frameworks.
U.S. Citizenship
Ability to obtain and maintain a federal security clearance.
Ability to pass a Federal background investigation.
Ability to pass pre-employment drug testing and demonstrate non-use of illegal drugs, including marijuana, for the 12 consecutive months preceding completion of the requisite Questionnaire for National Security Positions (QNSP).

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.
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.
Apply 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.
Advance applied research in adapting and aligning foundation models, designing advanced reasoning architectures, and enhancing the performance, behavior, or capabilities of agentic frameworks.
Apply expertise in training, alignment, parameter-efficient tuning, and augmenting LLMs/VLMs, or designing novel agentic architectures with advanced routing, retrieval, tool integration, and state-space representation.
Investigate and transition enhanced AI capabilities for complex, mission-specific reasoning, high-consequence decision support, reasoning over unstructured or semi-structured knowledge bases, and mission-informed tasks operating under real-world constraints.
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.
Apply expertise in 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.
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.