Applied Data Scientist 3

Pacific Northwest National Laboratory•Richland, WA

4d•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, 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 Emerging Threats and Technologies Division, part of the National Security Directorate, consists of over 400 scientists, engineers, and analysts with backgrounds in cyber, nuclear, intelligence, policy, data science, and other fields. We work in interdisciplinary project teams to provide innovative concepts that integrate policy, analytics, science, and technology into unique solutions. ETT delivers threat-informed approaches to research and development (R&D) and a culture of research to operations to harness the opportunities from emerging and disruptive technologies while at the same time countering the threats that arise from them. Our teams address complex national security problems by applying cutting-edge data science and leverage PNNL’s broad research capabilities to generate insight on emerging threats and technologies. We are seeking a Data Scientist with expertise in AI and a passion for solving mission-critical challenges to join our team. They will be a key member of an interdisciplinary team, focused on delivering data-driven solutions that address critical national security challenges within the nuclear nonproliferation, policy, and emerging technology domains. This individual will collaborate with peers to apply AI and machine learning models, analyze datasets, work with domain experts for applied use alignment, 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 5+ years of relevant work experience -OR- MS/MA and 3+ years of relevant work experience -OR- PhD with 1+ year of relevant experience
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. In addition, 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).
Note: Applicants will be considered ineligible for security clearance processing by the U.S. Department of Energy if non-use of illegal drugs, including marijuana, for 12 months cannot be demonstrated.
This position is a Testing Designated Position (TDP). The candidate selected for this position will be subject to pre-employment and random drug testing for illegal drugs, including marijuana, consistent with the Controlled Substances Act and the PNNL Workplace Substance Abuse Program.
Mandatory Requirements: Please be aware that the Department of Energy (DOE) prohibits DOE employees and contractors from having any affiliation with the foreign government of a country DOE has identified as a “country of risk” without explicit approval by DOE and Battelle. If you are offered a position at PNNL and currently have any affiliation with the government of one of these countries, you will be required to disclose this information and recuse yourself of that affiliation or receive approval from DOE and Battelle prior to your first day of employment.

Nice To Haves

Demonstrated ability to rapidly assess ambiguous situations, exercise sound judgment with limited time/inputs, and communicate well-considered recommendations.
Experience applying traditional statistical methods, ML, and AI to unimodal and multimodal open-source data (e.g., text, image, audio, video, graph), including preprocessing, representation/encoding, and task-specific modeling/decoding.
Experience with scientific data modalities include microscopy, radiation spectra, or mass spectrometry.
Strong proficiency in Python and experience with ML/AI frameworks (e.g., PyTorch, TensorFlow, Hugging Face).
Experience navigating research codebases (e.g., notebooks, prototype scripts) and translating them into maintainable, production-ready components.
Experience designing and deploying scalable ML pipelines or AI-enabled tools in operational or mission-critical environments (on-prem and/or cloud).
Experience in data management for AI applications including system design, version control, and experimental dataset curation.
Excellent communication and cross-functional collaboration skills; ability to bridge research, engineering, and domain stakeholders.
Proficiency in at least one general-purpose programming language (e.g., Python, R, Julia, Java, C/C++).
Experience working with sensitive and/or classified data in a national security context (preferred).
Demonstrated experience applying Intelligence Community Directives pertaining to collection and disseminating all-source intelligence analysis.
Experience leading small to mid-sized teams (approximately 5+ staff) to deliver applied technical work.
Experience briefing non-technical audiences.

Responsibilities

Design and implement AI/data science solutions to address complex national security problems, with a focus on nuclear nonproliferation, strategic policy analysis, and emerging/disruptive technology assessment.
Design and implement AI/data science solutions to address complex technical challenges, including all-source analysis, object detection, data fusion, and end-to-end data science workflows.
Design, develop, and implement methods, processes, and systems to analyze diverse datasets, including approaches that traverse and integrate modalities.
Demonstrate ability to transfer skills across application domains with a deployment-focused approach, specifically in support of non-proliferation mission.
Develop and evaluate predictive models and advanced algorithms to extract actionable value from structured and unstructured data.
Identify and assess domain-relevant data resources; translate findings into actionable technical approaches and mission-relevant capabilities.
Apply machine learning, data modeling, and software engineering to integrate and clean data, quantify uncertainty, identify patterns, and generate insights from high-dimensional datasets.
Understanding how to traverse the nexus of policy, data science, and software engineering to develop data science solutions against real-world constraints.
Deliver solutions driven by exploratory data analysis and rapid prototyping, with a focus on transition to operational use.
Build and maintain external partnerships that strengthen the team’s technical reputation and align outcomes with sponsor priorities.
Serve as a principal investigator (PI) or co-PI on projects and tasks that integrate multiple capabilities and/or interdisciplinary approaches.
Mentor and guide junior staff, fostering technical excellence and professional development.