SME Functional Lead
4 weeks ago
The SME Functional Lead for Imagery Analysis and Sensors will provide expert-level guidance and leadership in the development and delivery of training focused on imagery analytic tradecraft, methodology, and technology. Key focus areas include imagery analysis, imagery exploitation systems (such as RemoteView and Orchestration Services), and GEOINT data sources, including FMV, Spectral, OPIR, SAR, and TIR.
Responsibilities
Lead the development and delivery of training focused on imagery analysis, exploitation systems, and sensor data sources.
Provide instructional oversight on courses related to imagery exploitation systems, including RemoteView, Orchestration Services, and other critical GEOINT tools.
Guide training in the analysis and interpretation of various GEOINT data sources, including FMV, Spectral, OPIR, SAR, and TIR.
Supervise and mentor a team of instructors, ensuring content quality and alignment with NGA and IC operational needs.
Manage Mobile Training Teams (MTTs) and coordinate course delivery at both NGA facilities and other training locations worldwide.
Collaborate with government stakeholders to align training programs with mission objectives and emerging technologies.
Requirements
Current TS/SCI Clearance
Counterintelligence Polygraph (Preferred)
National Geospatial-Intelligence College (NGC) Instructor Certification (Preferred)
Bachelor's or Master's degree in geospatial analysis, geography, or a related field.
10+ years of experience in imagery analysis, including working with tools such as RemoteView, Orchestration Services, and other imagery exploitation systems.
Proficient in the use and analysis of various sensor data sources, including FMV, Spectral, OPIR, SAR, and TIR.
Experience developing and delivering training programs, particularly within NGA, the DoD, or the Intelligence Community.
Demonstrated ability to manage and lead a team in a training and operational environment.
Familiarity with NGA/IC product standards, imagery analysis workflows, and target generation processes.
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