Senior Data Scientist (54662

Senior Data Scientist

The Center for Geospatial Solutions (CGS) is seeking a Senior Data Scientist to provide technical expertise for complex geospatial data science, remote sensing, and environmental modeling projects. This role will help design, improve, and oversee end-to-end analytical workflows that turn large and varied geospatial datasets into reliable, decision-ready information.

Reporting to the Associate Director of Data Science, the Senior Data Scientist will work closely with data scientists, AI engineers, cloud engineers, project managers, and subject-matter experts. The position will collaboratively lead technical planning, guide implementation, troubleshoot difficult problems, and ensure that methods, validation, and documentation meet a high standard of scientific and client-facing quality.

The successful candidate will combine deep applied expertise with the ability to enable and empower others. They will translate complex scientific and technical questions into practical workflows, mentor technical contributors, and advance research and development that improves our methods, efficiency, and impact across wetlands, water, conservation, infrastructure, and other mission-motivated applications.

CGS was established in 2020 at the Lincoln Institute of Land Policy, which seeks to improve quality of life through the effective use, taxation, and stewardship of land. A nonprofit private operating foundation whose origins date to 1946, the Lincoln Institute researches and recommends creative approaches to land as a solution to economic, social, and environmental challenges. Through education, training, publications, and events, the Lincoln Institute integrates theory and practice to inform public policy decisions worldwide and has office locations in Cambridge, Massachusetts;
Washington, DC;
Phoenix, Arizona; and Beijing, China.

Technical Expertise and Workflow Design

• Lead collaboratively the design of end-to-end geospatial data science and remote sensing workflows, from problem definition and data acquisition through modeling, validation, interpretation, and delivery.
• Translate project goals and scientific questions into clear plans, technical requirements, milestones, and quality standards.
• Guide the selection and use of authoritative datasets, remote sensing products, geospatial methods, statistical approaches, and machine learning techniques.
• Anticipate risks, resolve complex technical issues, and make pragmatic discernments that balance scientific rigor, delivery needs, and available resources.
• Support technical members to refine common processes and establish repeatable methods across projects.

Scientific Quality and Validation

• Design or oversee accuracy assessments, validation strategies, sampling approaches, uncertainty analyses, and other quality-control methods.
• Ensure methodologies are reproducible, well documented, and appropriate for the intended use and context.
• Review code, models, data products, technical reports, and client deliverables for scientific and analytical quality.
• Clearly communicate methodological limitations, uncertainty, and appropriate interpretation of results to technical and non-technical audiences.

Team Enablement and Technical Delivery

• Enable data scientists and other technical contributors to execute defined processes independently and consistently.
• Provide hands-on troubleshooting, code review, technical guidance, and mentoring across multiple projects.
• Develop templates, reusable code, documentation, and training materials that strengthen team capability and reduce delivery risk.
• Work closely with project managers to estimate effort, plan technical work, manage dependencies, and keep delivery aligned with scope and schedule.

Research, Development, and Organizational Impact

• Foster, or contribute to, research and development that improves CGS methods, model performance, processing efficiency, and data products.
• Evaluate emerging datasets, geospatial foundation models, cloud capabilities, and systematic methods for practical use at CGS.
• Contribute technical expertise to proposals, scopes of work, client presentations, publications, and strategic partnerships.
• Represent CGS in technical discussions with clients, partners, funders, government agencies, and the broader scientific community.

• Ph.D. or Master's degree and equivalent experience in data science, geography, remote sensing, hydrology, environmental science, engineering, computer science, or a related quantitative field.
• Experience conducting the full research life cycle, including hypothesis development, experimental design, execution, and communication of findings.
• 5 or more years of professional experience applying geospatial data science, remote sensing, environmental modeling, or a closely related field to solve real-world problems and address stakeholder needs.
• Demonstrated experience designing and stewarding complex analytical workflows and enabling others to execute them…