Senior Fraud Analytics Consultant

Analytica•Bethesda, MD

About The Position

Analytica is seeking a Senior Fraud Analytics Consultant to provide domain expertise supporting fraud, identity theft, fabricated entity, information return fraud, and emerging scheme analytics. This role will guide analytical interpretation, validate model and rule outputs through return-level or case-level review, identify fraud patterns and filing behaviors, support stakeholder review sessions, and help translate analytical results into actionable treatment, mitigation, and operational recommendations. Analytica has been recognized by Inc. Magazine as a fastest-growing private US small business. We work with U.S. government customers in health, civilian, and national security missions. Analytica offers competitive compensation with opportunities for bonuses, employer paid health care, training and development funds, and 401k match.

Requirements

Bachelor's degree in Mathematics, Statistics, Computer Science, or related field.
Minimum 5 years of experience in fraud analytics, identity theft analysis, financial crime analytics, compliance analytics, or related program support.
Experience using Python, SQL, SAS, and/or R for model implementation.
Demonstrated experience supporting fraud analytics activities within a federal agency, financial institution, or highly regulated environment.
Working knowledge of statistical analysis, machine learning, anomaly detection, network analysis, supervised and unsupervised fraud detection approaches, or risk scoring techniques.
Must have active or ability to obtain IRS MBI clearance.

Responsibilities

Provide fraud analytics domain expertise to guide analytical development, model interpretation, rule evaluation, and operational decision-making across program use cases.
Analyze fraud schemes, filing behaviors, treatment processes, and return-level/case-level patterns to help distinguish identity theft, fabricated entities, and other emerging risks.
Support development, refinement, and monitoring of predictive models, business rules, filters, and analytical measures used to detect fraud and identity theft in pre-refund processing.
Prepare clear analytical summaries, briefing materials, dashboards, discussion points, and documentation for stakeholder reviews, leadership inquiries, operational meetings, and oversight requests.