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Geospatial Analyst
Company | Leidos |
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Location | Reston, VA, USA |
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Salary | $80600 – $145700 |
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Type | Full-Time |
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Degrees | Bachelor’s, Master’s |
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Experience Level | Senior, Expert or higher |
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Requirements
- Bachelor’s degree and 8+ years of related experience or Masters with 6+ years of related experience
- 12+ years of relevant experience in Geospatial Analysis, Intelligence Community, geospatial data formats (vector and raster data), intelligence fusion analysis, creating geospatial intelligence products, familiarity with various network domains, GIS software (ESRI ArcGIS Pro, ESRI ArcGIS Enterprise, ERDAS Imagine, RemoteView), and NGA data products and standards
- Experience in lieu of degree
Responsibilities
- The collection and analysis of geospatial data (vector and raster) from various data sources and the use of commercial and NTM source data to provide geospatial data preparation in support of geotechnical characterizations and test bed analysis.
- Collect, document and maintain geospatial data within data file structures and enterprise geodatabases in support of geospatial and geotechnical analysis efforts.
- Develop geospatial products and solutions to support geologic and engineering analysis.
- Collaborate with intelligence analysts to ascertain analytical workflows, business requirements, and to train personnel in the use of ArcGIS tools.
- Provide support to data capturing and conversion of GIS data for all GIS activities.
- Use various source data for research to perform imagery analysis of panchromatic/multispectral imagery, geospatial rectifications and development of elevation data sets.
Preferred Qualifications
- Python programming experience.
- Experience using ArcPy and ArcGIS API for Python to develop scripts and applications to analyze data and automate data processes.
- Experience using ArcGIS Enterprise to automate develop GIS applications, geoprocessing services, and web maps.
- 3D modeling experience using ArcGIS and other applications; experience processing and analyzing point cloud data.