The Travel Modeling Intern will provide support to the Analytics division in the MAG Planning Department. MAG’s Planning Department oversees transportation planning, programming, policy, data analytics, and community planning for the Metropolitan Planning Organization (MPO) in Utah County and the Rural Planning Organization (RPO) in Summit and Wasatch Counties, providing a forum for discussion and cooperation among local government representatives concerning region-wide issues.
This role involves preparing and updating regional travel demand model input files in Bentley’s Cube software, as well as other GIS data, maps, and tools to support regional forecasting and planning efforts. Tasks may also include data processing tasks in Python, R, Excel, or other data analysis software packages. Further tasks will involve running model scenarios and processing results for communication to broader stakeholders.
This is a part-time, up to 19 hours per week position expected to last no more than 6 months. Resume and cover letter must be submitted at mountainland.bamboohr.com/careers
Responsibilities:
Prepare input GIS data for the MAG forecasting models, which influence population projections and projects included in the Regional Transportation Plan (RTP).
Process and consolidate land use and transportation data for Summit, Utah, and Wasatch Counties.
Prepare transportation network input files for travel model scenario development purposes.
Run and process regional travel demand model scenarios.
Produce high-quality maps and datasets intended for key stakeholders.
Support GIS needs in other divisions in the MAG Planning Department.
Other duties as assigned.
Qualifications:
Working towards a BS or MS degree in geography, urban planning, civil engineering, statistics, data science, or other related discipline
Experience working in Esri GIS software (ArcGIS Pro, ArcGIS Online)
An understanding of regional transportation and land use planning in Utah County
Experience using Google Workspace
Familiarity with programming tools (e.g., Python, R, HTML, etc.)
Willingness and ability to quickly learn new skills and proactively consider solutions to complex problems.
Proactive, detail-oriented attitude
Availability to work an average of 19 hours per week
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