Environmental Modeler

Stone Environmental Inc.

Location: Montpelier, VT

Type: Full Time

Education: Master's Degree

Experience: 3 - 5 Years

The Environmental Systems Modeling (ESM) team at Stone Environmental is seeking a highly qualified
and motivated individual with a background in engineering and/or physical sciences and excellent
quantitative skills, with experience in environmental modeling, scientific computing, and one or more of the
following: GIS/spatial analysis, database analysis, or statistical analysis.

The ESM team is a group of diverse, highly motivated environmental scientists, engineers, GIS specialists,
and computer software developers, who specialize in applying both established and custom-designed models
and modeling tools to complex environmental problems. We work for a broad range of client organizations
in a variety of sectors and industries, who value our expertise, innovation, and high-quality products.
Projects range from locally focused assessment of agricultural best management practices (BMPs) to
national-scale water quality assessments. We also work with other teams at Stone to improve our
understanding of environmental processes by collecting and analyzing field data for use in modeling
investigations, creating web applications and database management strategies to improve user access to
information, and performing modeling analyses to assist in engineering and design efforts.

As part of the ESM team, this person will support environmental and agricultural modeling projects, where
general responsibilities may include the following:
 Application of air and water quality models at field, farm, and watershed scales;
 Computer programming to enable efficient processing of environmental datasets and model
 Data compilation and analysis;
 Integrating spatial analysis and mathematical modeling in environmental and agricultural sciences;
 Preparation of high-quality project deliverables, including technical reports and presentations, as well
as journal articles and literature reviews;
 Collaboration with team members and clients to understand and meet project goals and objectives.
Preferred Qualifications
 Experience in application of hydrologic, agronomic, atmospheric, or other environmental models;
 Scientific computer programming, with proficiency in at least 1 of: Python, R, FORTRAN, VB.NET,
or C#;
 Experience with relational databases such as PostgreSQL, Microsoft SQL Server, or Microsoft Access;
 Practical applications of spatial analysis software (ArcGIS, QGIS);
 Experience performing analysis with large national-level environmental datasets including: NLCD,
CDL, SSURGO, NHDplus, gridded weather data, pollutant monitoring data;
 Knowledge of agronomic practices in the United States, Canada, and Europe;
 Statistical or probablistic analysis techniques;
 Excellent written and verbal communication skills;
 Ability to manage time and work on multiple projects concurrently;
 Ability to problem solve and determine steps needed to accomplish high level tasks;
 Ability and willingness to learn new skills and take on new challenges.
 Other administrative duties as assigned.

Working Conditions
 Primarily office/computer-based with no essential physical requirements. Opportunities to participate
in occasional field work exist but are not required for this position.
 Based primarily in our Montpelier office, with flexibility for part-time remote work. Full time remote
options may be considered. Work hours are flexible, but typically occur during ‘normal’ weekday
business hours.
 Members of our team often attend conferences and meetings requiring some travel; willingness to
participate is desired but not required.

Experience and Education
 Master’s degree or higher in the physical sciences (e.g., agricultural/biological engineering,
civil/environmental engineering, hydrology, atmospheric science, chemistry, or related
environmental/geospatial field).
 Three to five years of post-graduate experience in a scientific or consulting position in a relevant field
is required. Additional advanced degrees may substitute for work exp

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