Data Scientist III - GEOINT
Listed on 2025-12-25
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IT/Tech
Data Scientist, Data Analyst, Data Science Manager, AI Engineer
Overview
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 AI and Data Analytics Division, part of the NSD, 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 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.
Key Responsibilities- Drives the execution of research by developing, testing, and deploying ML models and geospatial analytics workflows.
- Takes ownership of defined tasks or small projects, proactively identifying technical challenges and proposing solutions to senior staff or project leads.
- Engages with stakeholders to understand project requirements and translate them into actionable technical approaches aligned with sponsor goals.
- Serves as a mentor to junior staff or interns within the team, fostering a collaborative and inclusive research environment.
- Supports proposal development and business development by contributing to proposals and/or briefing sponsors.
- Builds effective working relationships within your immediate team, as well as across interdisciplinary teams at the group or division level.
This position is based in either Richland, WA or Seattle, WA and requires an onsite presence.
QualificationsMinimum Qualifications:
- 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
Preferred Qualifications:
- 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 in applying ML techniques to analyze hyperspectral data fusion for GEOINT applications.
- Hands‑on experience with geospatial analysis tools and machine learning frameworks, such as Python, Tensor Flow, PyTorch, or equivalent.
- Demonstrated proficiency in creating proposals and technical reports.
- Proven ability to collaborate effectively with a multi‑disciplinary team…
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