Hybrid GIS & Habitat Research Intern

Metropolitan Council; Saint Paul (MN); Hybrid; USD 21,000 - 34,000; Part time

Job summary

The Metropolitan Council offers an internship in the Community Development Research department focused on modernizing regional habitat classification for the Twin Cities seven-county area. You will label datasets, perform GIS work with satellite imagery, and validate classifications through field ground-truthing as part of a pilot study.

Hybrid onsite/remote work is available. Ideal candidates are in Data Science or Earth/Environmental fields, with GIS skills and an interest in public service.

Qualifications

• Must be enrolled in an accredited institution OR a recent graduate (within 12 months).
• Residence must be in Minnesota or Wisconsin during the internship.
• Unofficial transcript required to be attached to the application.
• Valid MN/WI driver’s license required.

Responsibilities

• Create labeled training and validation datasets for a machine learning habitat classification project across the Twin Cities region.
• Digitize and label habitat polygons in GIS using satellite imagery and existing land cover data.
• Conduct field ground-truthing to verify habitat types and perform QA by comparing observations with satellite classifications.
• Support a pilot study by testing, refining, and documenting data collection procedures for regional deployment.

Skills

GIS experience

Natural systems + habitats

Independent work & teamwork

Attention to detail

Recent graduate or final year

Education

Data Science, Earth Science, Environmental Science, Geography, Forestry, Geospatial Science

Tools

ArcGIS

QGIS

Job description

The Metropolitan Council offers an internship in the Community Development Research department focused on modernizing regional habitat classification for the Twin Cities seven-county area. You will label datasets, perform GIS work with satellite imagery, and validate classifications through field ground-truthing as part of a pilot study.

Hybrid onsite/remote work is available. Ideal candidates are in Data Science or Earth/Environmental fields, with GIS skills and an interest in public service.