Geospatial Data Science Intern: Modeling & Analysis

National Laboratory of the Rockies

Ümraniye

On-site

TRY 2,167,000 - 3,466,000

Part time

4 days ago

Be an early applicant

Application generator

Stand out for this role — generate a tailored resume and cover letter in about a minute.

Get past ATS filters

Benefits offered by this job

Medical insurance

Dental insurance

Vision insurance

403(b) employer match

Job summary

The National Laboratory of the Rockies (NLR) invites applications for a Graduate Year-Round Intern in Geospatial Data Science Modeling and Analysis. The role supports the Geospatial Data Science team within the Strategic Energy Analysis Center, focusing on energy deployment, big data, and geospatial modeling.

You will work with researchers to build and validate analytical solutions, conduct Python programming, and contribute to data preparation, literature reviews, and visualization, while

Qualifications

Minimum 3.0 GPA.
Undergraduate must be enrolled full-time in a bachelor’s program.
Graduate/PG: enrolled full-time in master’s or PhD; eligible for internship up to 1 year.

Responsibilities

Manipulate data sources and models for decision support and data analysis.
Prepare and process geospatial data with open-source tools.
Conduct background research on data sets and modeling approaches.
Develop literature reviews under supervision of researchers.
Program and script in Python to analyze and visualize data.
Work in HPC and cloud environments.

Skills

Geospatial data analysis

Data wrangling

Scientific programming

Communication skills

Independent work

Education

Bachelor’s degree in Geography/GIS/Environmental Science/CS/Engineering

Current or recent enrollment in a Master’s or PhD program

Tools

Python

QGIS

GitHub

Linux/Unix

HPC/Cloud

Job description

You will work with researchers to build and validate analytical solutions, conduct Python programming, and contribute to data preparation, literature reviews, and visualization, while

Get your free, confidential resume review.

or drag and drop your file here.