Early-Career GIS Analyst

Gradient, a Geosyntec Company, is seeking a motivated and resourceful Early-Career GIS Analyst with experience in environmental data to apply relevant skills in GIS and relational database design and management, spatial analysis, programming, and/or data visualization to a diverse range of environmental project settings. You will have the opportunity to join our growing practice in our Charlottesville, VA office.

Gradient is an environmental and health risk sciences consulting firm specializing in environmental sciences, human and ecological risk sciences, product stewardship, and life sciences. Gradient's scientists have a variety of backgrounds in chemistry, engineering, toxicology, epidemiology, ecotoxicology, medical device and pharmaceuticals, exposure sciences, industrial hygiene, GIS, product safety and liability, and sustainability.

We invest in our people. Each employee is unique, and your career at Gradient will be too. We offer competitive pay and benefits, and well-being programs to support you and your family.

To Learn More Visit: http://www.geosyntec.com/careers/.

Review, standardize, and compile data.
• Build and maintain environmental databases.
• Prepare data summaries and maps.

• Bachelor's degree in engineering, natural sciences, or related field. (required)
• Advanced degree in engineering, natural sciences, or related field. (preferred)

• Experience using ArcMap and/or ArcGIS Pro, or ArcGIS Online in academic and applied project settings or equivalent combination of education and experience. (required)
• Prior internship experience in environmental engineering. (preferred)
• Experience with environmental media testing data or environmental management experience (EQuIS, etc). (preferred)
• Exceptional written and oral communication. (required)
• Experience with 3D subsurface modeling software (e.g. Leapfrog, Earth Volumetric Studio [EVS]). (preferred)
• Programming and/or coding experience (e.g., Python with Numpy, Scipy; Django, Pandas, or GeoPandas; Matplotlib; R; JavaScript; Power BI). (preferred)

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