Geospatial Data Science Intern — Modeling & Analysis

National Laboratory of the Rockies; Golden (CO); On-site; USD 45,000 - 71,000; Part time

Benefits offered by this job

Medical insurance

Dental insurance

Vision insurance

Job summary

National Laboratory of the Rockies is seeking a Graduate Intern in Geospatial Data Science Modeling and Analysis to support the GDS team in energy deployment research. You will help develop geospatial models, prepare data, and apply open-source tools to evaluate energy technologies from local to continental scales.

The role emphasizes Python programming, literature reviews, and collaborative work with researchers, software developers, and policy analysts in a cross-disciplinary setting.

Qualifications

• Bachelor's degree completed; enrolled in master’s or PhD program in Geography/GIS, Environmental Science, Computer Science, Engineering, or related field.
• GitHub portfolio with publicly visible coding projects required or explain in cover letter why not.
• Proficiency in Python and geospatial libraries (geopandas, numpy, scipy, shapely, pyproj).
• Experience with open-source geospatial tools; ESRI tools not used in this group.

Responsibilities

• Manipulate multiple data sources, models, and software workflows for decision support.
• Prepare and process geospatial data using open-source software and programmatic approaches.
• Conduct literature reviews and background research on data sets and modeling.
• Develop literature reviews under supervision of researchers.

Skills

Python

Geospatial modeling

Communication

Education

Bachelor's degree in Geography/GIS/CS/Engineering

Tools

QGIS

Linux

GitHub

Job description

National Laboratory of the Rockies is seeking a Graduate Intern in Geospatial Data Science Modeling and Analysis to support the GDS team in energy deployment research. You will help develop geospatial models, prepare data, and apply open-source tools to evaluate energy technologies from local to continental scales.

The role emphasizes Python programming, literature reviews, and collaborative work with researchers, software developers, and policy analysts in a cross-disciplinary setting.