Eastern Research Group
On-site Environmental Scientist, Engineer, and Technical Specialist
About this role
ERG seeks an environmental scientist or engineer to join its Morrisville, NC office, supporting federal, state, and commercial clients with data analysis and environmental assessment work. The role requires proficiency in programming languages like R or Python to process large environmental datasets and deliver scientifically rigorous analyses for monitoring and reporting.
What you'll do
- Process, analyze, and interpret environmental data using R, Python, MATLAB, or similar tools
- Manage and quality-assure large datasets for environmental monitoring projects
- Perform statistical analyses to support environmental assessment and reporting
- Communicate technical findings effectively to clients and stakeholders
- Support multidisciplinary teams on federal, state, and commercial environmental projects
- Prioritize and execute deliverables in a fast-paced consulting environment
What they're looking for
- Programming: R, Python, MATLAB, or equivalent
- Environmental data analysis and interpretation
- Statistical analysis and modeling
- Data quality assurance and management
- Large dataset handling and processing
- Technical writing and communication
- Environmental science or engineering principles
- Project management and prioritization
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Eastern Research Group
Eastern Research Group is a multidisciplinary research and consulting firm that helps communities and government agencies address water, wastewater, stormwater, and environmental challenges through infrastructure assessment, design, and project leadership. The company is hiring water and civil engineers at multiple experience levels, as well as combustion scientists, to deliver technical solutions and research support across water resources, environmental compliance, and infrastructure projects.
- Website
- erg.com
Likely interview questions
- Walk us through a recent project where you processed and analyzed environmental data—what tools did you use and what challenges did you encounter?
- How do you approach data quality assurance when working with large, complex environmental datasets?