The Senior Geospatial Intelligence (GEOINT) Analyst will perform advanced geospatial, topographic, and imagery analysis in support of Special Operations Forces (SOF) missions. The analyst will develop regional and point-based analytical products supporting the Find, Fix, Finish, Exploit, and Analyze (F3EA) targeting methodology and operational mission requirements.

Required Skills

Due to the sensitivity of customer related requirements, U.S. citizenship is required.

Active Top Secret security clearance with SCI eligibility/access (TS/SCI).

Minimum of 6 years of progressive experience supporting operational- and tactical-level intelligence missions, including complex and time-sensitive geospatial, topographic, and imagery analysis of ground features and remotely sensed data.

Experience in targeting, intelligence, and/or geospatial systems.

Proficiency with Geographic Information System (GIS) applications and intelligence-related automation tools used to support analytical efforts and product development.

Broad understanding of intelligence collection processes and collection management.

Experience performing geospatial processing and developing innovative methodologies to solve complex tactical intelligence problems.

Proficiency with standard computer applications, including Microsoft Office.

Strong demonstrated briefing and communication skills, with the ability to maintain professionalism in operational environments.

Self-motivated and capable of managing multiple priorities simultaneously while making sound decisions in high-stress, time-sensitive environments.

Desired Skills

Proficiency in integrating GEOINT with other intelligence disciplines to support comprehensive intelligence analysis.

Working knowledge of how geospatial techniques and capabilities support the Find, Fix, Finish, Exploit, and Analyze (F3EA) targeting cycle.

Working knowledge of computer scripting or programming languages such as Python, JavaScript, HTML, R, or SAS.

Previous experience supporting the Special Operations Forces (SOF) community in a role relevant to the labor category is highly desirable.