Data Scientist II

LINCOLN INSTITUTE OF LAND POLICY•Washington, DC

7d•$76,000 - $95,000•Remote

About The Position

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.

Requirements

Master’s degree or equivalent experience in data science, geography, remote sensing, environmental science, engineering, computer science, or a related quantitative field.
2-5 years of professional experience applying geospatial analysis, data science, remote sensing, or environmental modeling to solve real world problems and address stakeholder needs
Proficiency in Python for data engineering and data science workflows, including experience with common geospatial and scientific libraries.
Experience with raster and vector data, GIS software such as Esri or open-source equivalents, and large geospatial datasets.
Strong foundation in statistics, data science, machine learning, and remote sensing.
Experience acquiring, cleaning, evaluating, and documenting data from multiple sources.
Experience independently designing and implementing GeoAI models and other analytical approaches, addressing open-ended problems with incomplete or evolving requirements.
Experience with Git/GitHub or comparable version-control workflows.
Strong attention to detail and commitment to reproducible, well-documented work.
Clear written and verbal communication skills and the ability to collaborate effectively in a fully remote environment.
Collaborative and able to work successfully in interdisciplinary teams with colleagues from various topical backgrounds and different skill levels and communication levels
Exceptional critical thinking skills with the ability to deconstruct complex problems, prioritize issues, and implement sensible solutions
Experience translating client needs into clear milestones, scopes of work, and risk assessments
Strong ability to communicate technical and computational concepts clearly to non-technical audiences, including domain experts, stakeholders, and partners
Self-motivated and goal-oriented with the ability to take an innovative, strategic, and evidence-based approaches to research and empathetic collaboration
Willingness and ability to learn new frameworks, data structures, and infrastructure
U.S. Citizen, or legally authorized to work in the United States with no need for future sponsorship

Nice To Haves

Experience with hydrology, geomorphology, terrain analysis, wetlands, ecology, or other environmental domains.
Experience with cloud-based processing using AWS, Azure, Google Cloud, Google Earth Engine, or similar platforms.
Experience with geospatial foundation models, embeddings, or large-scale Earth observation datasets.
Experience contributing to academic or applied research, including study design, analysis, and communication of findings.
Experience with field data, wetland delineations, survey data, or validation datasets.
Experience supporting government, nonprofit, or consulting projects and working within defined scopes and deadlines.

Responsibilities

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.
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.
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.
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.

Benefits

3x employer contribution towards retirement matching your employee contribution up to 15%
health insurance with no deductible
dental insurance
vision insurance
copay assistance through an employer-funded health reimbursement account
short-term disability coverage
long term disability coverage
paid parental leave
voluntary insurances such as accident insurance
health care flexible spending
dependent care flexible spending
paid time off for holidays, vacation, personal, sick, bereavement, and jury duty
office closure between December 24 Jan 1 each calendar year
flexible schedule and option for a compressed 4 day workweek
tuition and staff development reimbursement
pet insurance
Employee Assistance Program