$96,533–$110,336.20 Per Year
Analysis Skills, Bayesian Networks, Budgeting, Civil Engineering, Climate Change, Data Analysis, Data Collection, Data Management, Data Modeling, Data Sets, Deep Learning, Environmental Engineering, Environmental Sciences, Geological Engineering, Geological Mapping, Groundwater Modeling, Hydraulic Engineering, Hydrology, Laboratory Management, Machine Learning, Project Evaluation, Proposal Writing, Site Evaluation, Software Engineering, Software Simulation, Spatial Data, Statistics, Team Player, Transportation Modeling, Trend Analysis, Willing to Travel
Name of Employer: GSI Environmental Inc.
Position Location: 2000 Powell Street, Suite 820, Emeryville, CA 94608.
Telecommuting is permitted, but applicants must live within a reasonable commuting distance.
Salary: $96,533.00 - $110,336.20 per year
Hours: Monday - Friday, 8:00 am to 5:00 pm
Summary of Duties:
- Research, acquire, compile, and manage data for environmental projects.
- Evaluate environmental project data and information to assess site condition.
- Coordinate and oversee field and laboratory programs.
- Perform computer modeling and data analysis to develop solutions to environmental problems.
- Prepare documentations and reports.
- Assist PTLs and Principals with preparation of proposals (scopes of work and budgets).
- Participate in environmental project team meetings.
- Develop professional network by participating in professional societies and conference attendance.
Education requirements: Bachelor's degree in Civil Engineering, Environmental Engineering, or related field or foreign equivalent.
Experience requirements: 2 years of experience in the job offered or related role.
Special Skills or Other Requirements: 2 years of experience must include:
- Landslide and debris flow simulation software, civil engineering, and geological hazard assessment.
- Hydrologic and hydraulic (H&H) modeling for flood mapping, groundwater modeling, and sediment transport analysis.
- Statistical analysis of large climate datasets, including trend analysis, Bayesian approach, and climate change analysis.
- Machine learning and deep learning models to analyze groundwater level and streamflow, spatial data, and satellite images.
- Developing and applying numerical models (Finite Difference/Finite Volume) for hydraulic and structural integrity analysis for dam safety and breach modeling.
- Unsupervised clustering and classification techniques for geospatial data, including soil types and geological mapping.
- Freshwater modeling.
Travel requirements: 5% domestic travel and 5% international travel.