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Intelligencecareers

GEOINT Hybrid Analyst (Rapid Response Data Officer)

Intelligencecareers, Georgia Center, Vermont, United States,


GEOINT Hybrid Analysts analyze and interpret the full spectrum of spatial data to support U.S. military and policymaker interests. They combine an understanding of geospatial data and imagery analysis to characterize events, discover relationships and trends, and produce geospatial-intelligence. These analysts conduct multi-INT research and descriptive analyses.MANDATORY QUALIFICATION CRITERIA:

For this particular job, applicants must meet all competencies reflected under the Mandatory Qualification Criteria to include education (if required). Online resumes must demonstrate qualification by providing specific examples and associated results, in response to the announcement's mandatory criteria specified in this vacancy announcement:Experience providing intelligence analysis concerning threat networks for dynamic mission sets, such as Special Operations, and/or Intelligence Community.Experience coding and an understanding of software/algorithm development.Demonstrated experience working with non-traditional data sources such as Internet of Things data, sensor data, and associated tools.Extensive experience with GIS to include data integration, extraction, and management.Demonstrated experience reading and understanding intelligence issues, military affairs, and using GIS to develop Geospatial Intelligence reports and products to solve problems.Demonstrated experience in requesting and reviewing imagery, collection processes, and correlating various data sources in support of ongoing operations.EDUCATION REQUIREMENT:A. Education: Bachelor's degree from an accredited college or university in Cartography, Computer Science, Geographic Information Systems (GIS), Geography, Remote Sensing, Data Analytics, or a related field.-OR-B. Combination of Education and Experience: A minimum of 24 semester (36 quarter) hours of coursework in any area listed in option A, plus experience working in an Intelligence discipline requiring analysis and interpretation of GEOINT data, or related area that demonstrates the ability to successfully perform the duties associated with this work. As a rule, every 30 semester (45 quarter) hours of coursework is equivalent to one year of experience. Candidates should show that their combination of education and experience totals 4 years.-OR-C. Experience: A minimum of 4 years of experience working in an Intelligence discipline requiring analysis and interpretation of GEOINT data, or a related area that demonstrates the ability to successfully perform the duties associated with this work.PHYSICAL REQUIREMENT:

Distinguish principal colors and shades/hues of principal colors; Near visual acuity of 20/20 or better with or without corrective lenses.DESIRABLE QUALIFICATION CRITERIA:

In addition to the mandatory qualifications, experience in the following is desired:Leadership experience in a deployed combat zone.Demonstrated experience working with and applying technical skills, such as computer vision implementation, data mining and analytics, data visualization, statistical analysis, algorithm development, or data science in support of a mission requirement.Experience with the GEOINT exploitation and analysis, data analytics against Key Intelligence Questions, and understanding and experience with the NGA production/publication processes, and Source operations.Experience correlating multiple sources of intelligence to derive entities and associations for target development, with GEOINT services and publications to include baseline reports and other GEOINT reporting.Experience working with a highly technical team to achieve realistic and timely goals in support of a broader mission imperative; ensure data meets relevant standards and is organized, current, authoritative, and appropriately maintained.Experience with digital cartography, image processing, computer technology, geographical information systems (GIS), geospatial production techniques, remote sensing, photogrammetry, and QT Modeler are appreciated.

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