

Mid-Level Analytic Methodologist 130-001

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IC-CAP LLC is a Woman Owned / HUBZone Small Business working in the Department of Defense and Intelligence Community. We are always looking for highly talented, energetic, and dynamic professionals that are interested in protecting the defense of our nation.
We are looking to fill this position at the following location(s):
- DC Metro Area
Job Description
*** Please note that this position is contingent upon the successful award of a contract currently under bid.***
The Mid-Level Analytic Methodologist supports DIA's Directorate for Analysis (DI) in developing, testing, and institutionalizing advanced analytic methodologies that strengthen intelligence tradecraft rigor, reduce cognitive bias, and accelerate decision advantage across the Defense Intelligence Enterprise (DIE). This role operates within the SAFe Agile framework and contributes directly to deliverables including methodology documentation, training materials, and prototype analytic capabilities.
Duties may include:
Design and deploy structured analytic techniques (SATs) to actively mitigate cognitive bias and improve the rigor and defensibility of all-source intelligence assessments across the DIE per ICD 203 Analytic Standards.
Research, develop, and implement advanced AI-assisted analytic techniques including predictive modeling, NLP, and pattern recognition to increase timeliness and accuracy of intelligence production.
Collaborate with data scientists and engineers to integrate multi-INT data streams (GEOINT, SIGINT, HUMINT, OSINT, cyber) into unified analytic workflows enabling rapid correlation and non-obvious relationship discovery.
Support the Quality Assurance Framework by contributing to TEVV protocols for analytic models and AI systems, ensuring outputs are unbiased, explainable, and compliant with IC tradecraft standards.
Produce early-warning assessments of emerging technologies and disruptive analytic capabilities to ensure the IC maintains strategic awareness.
Author methodology documentation, analyst playbooks, and training materials Knowledge Transfer & Adoption; support delivery of training including mobile team instruction.
Participate in SAFe Agile ceremonies (PI planning, sprint reviews, retrospectives); contribute methodology-focused user stories aligned to Product Owner backlogs and Government priorities.
Support knowledge capture, documentation, and sharing; maintain searchable repositories of analytic techniques and lessons learned.
Education and Experience
Required:
Bachelor's degree in Political Science, Intelligence Studies, Data Science, Computer Science, or related field AND 3–6 years of experience in intelligence analysis or analytic methodology development in classified IC or DoD environments
Demonstrated experience applying structured analytic techniques (SATs) in all-source intelligence production; working knowledge of ICD 203 Analytic Standards
Experience integrating AI/ML tools into intelligence analytic workflows; ability to evaluate predictive models for tradecraft compliance
Demonstrated ability to author analytic products, methodology documentation, training materials, and operator playbooks
Familiarity with Agile/SAFe development environments; ability to contribute user stories and participate in sprint ceremonies
Desired:
Familiarity with DIA analytic platforms: MARS, Palantir, or Object-Based Production (OBP) frameworks
Experience with Python, R, or SQL for analytic scripting, data manipulation, or model evaluation
Working knowledge of DIA's established software baseline: Python, R, SQL, ArcGIS, Tableau
SAFe Agile certification (e.g., SA, SP) or equivalent demonstrated SAFe program delivery experience
Prior DIA, NGA, CYBERCOM, or IC COCOM analytic assignment
Master's degree in a relevant field
Security Clearance:
Active TS/SCI and the willingness to sit for a polygraph, if needed
IC-CAP provides equal employment opportunities (EEO) to all applicants for employment without regard to race, color, religion, gender, sexual orientation, gender identity or expression, national origin, age, disability, genetic information, marital status.