Graduate Intern – Geospatial Data Science Modeling and Analysis

Jobtailor; Golden (CO); On-site; USD 85,000 - 115,000; Full time

Job summary

Jobtailor in Golden, CO seeks a geospatial scientist to support energy deployment research by modeling and analyzing spatial data. You will manipulate data sources, use open-source tools like QGIS and Python libraries, and contribute to distributed computing environments.

Collaborate with geospatial data scientists, software developers, and policy analysts to deliver analytical solutions for siting, deployment, and adoption in evolving energy systems.

Qualifications

• Must have completed a bachelor’s degree and either be enrolled in or recently graduated from a master’s degree, or currently enrolled in a PhD program, in Geography/GIS, Environmental Science, Computer Science, Engineering, or a related technical field
• Demonstrated independent programming experience in Python and libraries including geopandas, numpy, scipy, shapely, and pyproj
• Proficiency and experience with geospatial analysis and modeling techniques using open-source tools such as QGIS
• Experience with geographic transformations and projections
• Must submit official or unofficial school transcripts
• Letter of recommendation if selected

Responsibilities

• Support geospatial modeling and analysis for energy deployment research
• Manipulate multiple data sources, models, and software tools in scientific workflows
• Prepare and process geospatial data using open-source desktop software and programmatic approaches
• Program and script in Python to conduct analysis and visualize data
• Work in distributed computing environments, including internal servers, HPC, and the Cloud
• Collaborate with geospatial data scientists, software developers, and policy analysts

Skills

Python Programming

Geospatial Analysis

QGIS Proficiency

Data Manipulation

Collaborative Teamwork

Education

Bachelor’s degree with master’s/PhD in a related field

Tools

QGIS

Geopandas

Numpy

Scipy

Shapely

Pyproj

Cloud Computing

Distributed Computing

Job description

Support geospatial modeling and analysis for energy deployment research
Manipulate multiple data sources, models, and software tools in scientific and engineering workflows
Prepare and process geospatial data using open-source desktop software and programmatic approaches
Conduct background research on datasets, current modeling approaches, and existing tools
Develop literature reviews under the guidance of research scientists
Program and script in Python to conduct analysis and visualize data
Work in distributed computing environments, including internal servers, NLR’s high-performance computing system, and the Cloud
Assist geospatial scientists in developing analytical solutions for energy siting, deployment, and adoption
Collaborate with geospatial data scientists, software developers, and policy analysts

Requirements

• Minimum 3.0 cumulative grade point average
• Must have completed a bachelor’s degree and either be enrolled in or recently graduated from a master’s degree, or currently enrolled in a PhD program, in Geography/GIS, Environmental Science, Computer Science, Engineering, or a related technical field
• Must meet educational requirements prior to employment start date
• Must submit official or unofficial school transcripts
• Letter of recommendation required if selected
• Resume and online code repository such as GitHub with several publicly visible coding projects, or explanation in cover letter for not including them
• Demonstrated independent programming experience in Python and libraries including geopandas, numpy, scipy, shapely, and pyproj
• Proficiency and experience with geospatial analysis and modeling techniques using open-source tools such as QGIS
• Experience with geographic transformations and projections
• Ability to work in a dynamically evolving digital environment as part of a collaborative and often-dispersed team
• Critical thinking, analytical, research, written communication, and verbal communication skills
• Internships are 6–12 months
• Must be able to obtain and maintain a federal Personal Identity Verification (PIV) card for assignments extending beyond six months, including a favorable background investigation
• Must pass a pre-employment drug test
• Must comply with federal drug-free workplace requirements

Core Competencies

Demonstrates expertise in geospatial modeling and analysis, with strong programming skills in Python and proficiency in geospatial tools such as QGIS. Capable of collaborating effectively in a distributed computing environment while conducting thorough research and analysis.

Highest-signal resume keywords

• Python Programming
• Geospatial Analysis
• QGIS Proficiency
• Data Manipulation
• Collaborative Teamwork

ATS Optimization Keywords

Hard Skills

• Geospatial Modeling
• Data Analysis
• Geopandas
• Numpy
• Scipy
• Shapely
• Pyproj
• Geographic Transformations
• Open-Source Tools
• High-Performance Computing

Soft Skills

• Critical Thinking
• Analytical Skills
• Written Communication
• Verbal Communication

Certifications & Qualifications

• Personal Identity Verification (PIV) Card

Industry Keywords

• Geography
• GIS
• Environmental Science
• Energy Deployment
• Research

Tools & Technologies

• QGIS
• Cloud Computing
• Distributed Computing