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Senior Open-Source Intelligence Analyst- 54863-1

Arlington VA (Hybrid 4days onsite)

Contract role

We are seeking a Senior Open-Source Intelligence Analyst to join our team. The selected individual will need to live in the DC Metro area to report to HQ in Arlington VA in alignment with customer policy. The current policy is to telework 1 day per week and report in-office the rest of the week. The telework schedule can change as directed by the customer.
Additional Requirement:
Ability to travel up to 25 percent (within the DC metro area and out of the DC metro area)
Position Description Intelligence & Analytics
Identify, track, and monitor emerging fraud typologies across financial and operational channels using fraud and intelligence gathering expertise.
Conduct analysis of open sources to identify fraudulent communication channels and techniques, including, but not limited to forums, social media, dark/deep web, news media, public records, and geospatial data.
Build and maintain fraud indicators, risk scores, and watchlists using internal data and external intelligence sources.
Develop analytical queries, dashboards, and automated alerts to uncover anomalous patterns such as counterfeit documentation, suspicious claims activity, identity misuse, or operational irregularities.
Leverage open-source data and information to conduct link analysis to uncover fraud networks and schemes.
Cross-Functional Collaborations
Produce high-quality intelligence products including threat assessments, trend analyses, profiles, timelines, and geo-based heat maps.
Partner with internal stakeholders to share intelligence, escalate issues, and support audit and investigative efforts.
Identify issues and trends based on severity, potential impact, and risk, ensuring proper documentation and evidentiary standards.
Risk & Controls
Recommend and evaluate preventive, detective, and mitigative controls.
Monitor changes in policy, regulations, technology, and criminal trends to anticipate shifts in fraud risk.
Reporting & Communication
Deliver timely, actionable reporting to leadership on trends, exposures, root causes, and mitigation opportunities.
Translate analytical findings into clear recommendations for non-technical stakeholders.
Prepare materials for audit, compliance, or law enforcement requests as needed.
Position Requirements
Experience
MUST have a Bachelor s degree and at least 10 years of professional experience (preferred) as an open-source intelligence analyst and other related fields.
Professional certification (preferred), such as CFE, CIA, CISA, or similar.
Primary Requirements
Proven ability to conduct open-source intelligence (OSINT) analysis to identify, track, and monitor emerging fraud typologies across financial and operational channels.
Experience building and maintaining fraud indicators, risk scores, and watchlists using internal data and external intelligence sources.
Proficiency developing analytical queries, dashboards, and automated alerts to uncover anomalous patterns (e.g., counterfeit documentation, suspicious claims activity, identity misuse, operational irregularities).
Ability to leverage open-source data to conduct link analysis and identify fraud networks and scheme interdependencies.
Ability to produce high-quality intelligence products (threat assessments, trend analyses, profiles, timelines, geo-based heat maps) with clear analytical rigor and defensible findings.
Track record partnering with internal stakeholders (audit, investigations, and data personnel) to share intelligence, escalate issues, and support audit/investigative efforts.
Demonstrated capability to deliver timely, actionable reporting to leadership, translating analytical findings into clear recommendations for non-technical stakeholders.
Desired Knowledge, Skills, and Abilities (KSAs)
Robust knowledge of fraud schemes and typologies, regulatory frameworks, and fraud-detection methodologies.
Strong analytical skills and experience using key tools, such as Microsoft PowerBI, and other link and visualization tools.
Working knowledge of SQL and Python/R for data preparation, feature engineering, and anomaly detection.
Ability to translate operational observations into data insights.
Clear written and verbal communication tailored to non-technical audiences.
Excellent planning, organizational, and time management skills.