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Environmental Scientist/GIS Specialist

Employer
Applied Technology & Science
Location
California, Kentucky, US
Salary
Competitive
Closing date
Dec 12, 2022

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Sector
Consultancy/Private Sector
Field
Informatics / GIS
Discipline
GIS
Salary Type
Salary
Employment Type
Full time
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Job Description:
A-T-S is currently seeking an experienced GIS professional to join our team to support natural resources, engineering, and environmental science teams. Under general supervision, the GIS Specialist will be responsible for GIS services and coordinating GIS data sets with staff and contractors. The ideal candidate should have a background in using a variety of data analysis and data mining methods, building and implementing models, using and creating algorithms and scripts, and creating and running simulations, including a strong emphasis in using ESRI software with Python.

Responsibilities:

* Serve as GIS task lead for numerous large-budget, deliverable-driven environmental consulting projects.
* Responsible for integrating engineering, biological, cultural, and historical resource data into a standardized and centralized GIS database, managing the extensive GIS database, and providing accurate cartographic products
* Provide GIS analysis, environmental modeling, risk assessment, and database support to engineers, wildlife biologists, botanists, and staff scientists
* Create GIS deliverables for environmental impact reports, geological and cultural resources investigations, and environmental permitting applications
* Prepare clear and concise metadata, database, and procedural documentation and as update best practice workflow methodologies
* Perform QA/QC procedures on spatial datasets to verify spatial/metadata accuracy and document data sources

Requirements :

* B.S. in related field
* 0-5+ years of experience with manipulating data sets and building statistical models
* Experience with Python and GIS (looking for demonstrated ability to expand and automate the ESRI platform)
* Experience in Database Design
* Practical/applied machine learning experience
* Understanding of data structures and data pipelines
* Domain expertise in technical discipline outside of computer/data science (e.g., environmental science, climate change, hydrology, ecology) is highly desirable
* Statistics (Bayesian statistics background) is a plus
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