Senior Data Scientist III - GEOINT/Remote Sensing

Company: Pacific Northwest National Laboratory

Location: Richland, WA (Remote)

Type: Full-time

Remote: Yes

Posted: 2026-09-16

About this role

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, Integrated Discovery 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 National Security Directorate, 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.


Responsibilities
PNNL is seeking a Senior 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 ...

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