Geospatial Data Scientist II (54590)

Who We Are

The Center for Geospatial Solutions (CGS) is a self-sustaining nonprofit enterprise. Founded to help bridge the gap between policy and practice, our mission is to enable people and the planet to meet the pace of change by expanding access to new technologies that power more sustainable and equitable outcomes.

We are a fully remote team of award-winning professionals with decades of applied expertise and end-to-end GIS capabilities. By embracing whole-system thinking and state-of-the-art technology, we enable partners across public, private, and nonprofit sectors to tackle complex, real-world challenges—like housing affordability, ecosystem conservation, water management, and sustainable infrastructure—with greater clarity. Our work liberates and connects key information, creates nuanced pictures of complex situations, and makes land, water, and social data easier to use, understand, and act on. We use tools like satellite data and artificial intelligence to deliver insights for impact.

At CGS, we believe that technology can be a tool for positive change. We are dedicated to building a diverse team that represents the communities and systems we live and work in. If you’re excited about this role but don’t meet every listed qualification, we encourage you to apply. We value potential, curiosity, and lived experiences, and know a more inclusive team makes us a stronger organization.

About the Lincoln Institute

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.

Position Overview

The Center for Geospatial Solutions (CGS) is seeking a Data Scientist II to implement geospatial data science, remote sensing, and environmental modeling workflows that support real-world choices about land, water, conservation, infrastructure, and related challenges.

Reporting to the Associate Director of Data Science, the Data Scientist will acquire and evaluate data, run and improve analytical workflows, conduct accuracy assessments, document results, and help automate repeatable processing steps. The role will exercise sound judgment about data quality, appropriate methods, and issues that should be elevated to senior technical staff.

This position is well suited to an applied data scientist who is comfortable moving between geospatial analysis, Python-based processing, remote sensing, statistics, and collaborative project delivery. The successful candidate will be eager to deepen their expertise while producing reliable, reproducible work that can scale across projects and geographies.

What You Will Do

Geospatial Analysis and Workflow Implementation

• Implement established geospatial data science and remote sensing workflows from data acquisition through processing, analysis, model execution, validation, and delivery.
• Acquire, organize, clean, and evaluate raster, vector, tabular, terrain, and Earth observation datasets from public, partner, and client sources.
• Use Python, GIS software, and open-source tools to process large geospatial datasets and generate repeatable analytical outputs.
• Run geospatial machine learning or deep learning workflows, evaluate model outputs, and identify important performance issues or data limitations.
• Exercise judgment about the best available data, important caveats, and technical issues that should be elevated to senior technical staff.

Validation, Documentation, and Quality

• Conduct spatial statistics, accuracy assessments, quality-control checks, and validation using established methods.
• Prepare clear documentation of data sources, processing steps, code, assumptions, limitations, and results.
• Review outputs for completeness, consistency, and technical quality before they are shared with partners or clients.
• Contribute to reproducible project structures, data dictionaries, metadata, and technical handoff materials.

Automation and Process Improvement

• Identify repetitive or error-prone steps that can be automated, standardized, or made more efficient.
• Develop and maintain scripts, functions, notebooks, and reusable components that improve delivery speed and consistency.
• Work with senior data scientists, AI engineers, and cloud engineers to move useful prototypes toward scalable workflows.
• Test new datasets and methods and share practical findings with the broader technical team.

Collaboration and Delivery

• Work closely with senior technical staff, AI engineers, GIS professionals, project managers, and subject-matter experts.
• Communicate progress, technical considerations, results, and risks clearly in team meetings, written updates, and presentations.
• Contribute to client deliverables, proposals, technical memos, presentations, and demonstrations.
• Participate in peer review and contribute to an inclusive team culture focused on learning, quality, and impact.