Water Resource Scientist

Minnehaha Creek Watershed District | Posted Jan 25, 2024

Deadline: Feb 14, 2024


Contact:
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Experience Level:
0-5 Years
Link to Apply:
Apply Now

Who You Will Work With – The Team:
The Research and Monitoring Department’s success requires a dynamic, nimble team of driven, creative, critical thinkers. The team will use its expertise in data collection, data analysis, data visualization, and modeling to (1) draw deep data-driven insights that inform planning and decision-making and (2) develop exceptional written, verbal, and visual storytelling. As a Water Resource Scientist, you will collect field data and conduct data analysis to support critical MCWD projects and initiatives. You will report to the Research and Monitoring Manager and collaborate to implement MCWD’s mission, vision, and goals.

What You Will Be Doing – The Job:
Data Analysis to Develop Watershed Strategies
• Collecting water quality, hydrologic, and biological data to characterize the aquatic health in Minnehaha Creek Watershed District.
• Analyze water resource data to extract engaging data-driven insights.
• Develop watershed and lake models to help identify potential watershed restoration strategies.
• Lead work across programs to develop data insights and data-driven stories to help characterize the impact of MCWD’s projects on water quality and biological conditions.
Contribute to Research and Monitoring’s Planning, Strategy, and Implementation
• Assist in managing, evaluating, and updating the District’s Research and Monitoring strategy, workflow, and the design and implementation of project plans to support key initiatives.
• Collect water quality, hydrology, and biological data with other Research and Monitoring staff to support MCWD initiatives and projects.
• Research, learn, and implement novel data analysis, data visualization, monitoring, and modeling techniques to help MCWD more effectively identify water resource issues and implementation strategies.
• Identify ways to improve MCWD’s data collection workflows to improve efficiency and resource allocation.