​This is a full-time Fraud Data Analyst role at Amivero, supporting the federal government in developing fraud analytic models for critical, mission-driven IT systems. The analyst will be instrumental in using data analytics to inform program strategy, policy configuration, and the acquisition of new technology to counter evolving identity fraud threats within the customer’s ecosystem (likely Login.gov or similar federal identity services).

• ​Location: US (No specific state listed, but likely remote with federal context).
• ​Experience Required: Bachelor’s Degree plus 10 years of relevant experience. The ideal candidate is seasoned in Fraud/Identity operations.
• ​Clearance: US Citizenship required to obtain Public Trust.
• ​Focus: Developing and maintaining fraud models (identity fraud, account takeover, synthetic identity fraud), fraud risk assessment, anomaly detection, policy configuration tuning (LexisNexis), and KPI reporting/dashboarding (Tableau).

​What Your Day Might Include: Modeling, Risk, and Infrastructure

​The analyst operates across the full spectrum of fraud management, from developing models and conducting risk assessments to collaborating on data infrastructure improvements.

• ​Fraud Modeling: Develop and maintain fraud models to detect identity fraud, account takeover, and synthetic identity fraud. Incorporate relevant data from third-party technology providers to continuously improve and enhance these models.
• ​Fraud Analytics: Conduct data analytics on new account creation attempts and investigative findings to identify fraudulent trends and patterns. Monitor fraud analytics which may include Identify and Entity Resolutions/Detection, Social Network Analysis, Unsupervised Monitoring.
• ​Detection Systems: Establish in-range and out-of-range anomaly behaviors and indicators that will trigger action. Continuously monitor model performance as fraud schemes evolve.
• ​Strategy & Policy: Use data analytics findings to inform program strategy, LexisNexis fraud policy configuration tuning, team staffing levels, and the acquisition of new technology.
• ​Risk Management: Conduct fraud risk assessments to understand program vulnerabilities, establish risk tolerances, and develop risk responses. Develop a fraud response plan including scenario planning and exercises.
• ​Reporting & Collaboration: Support the development of dashboards in Tableau to report KPIs and suspicious activity alerts. Collaborate with DevOps and SecOps teams to improve the data infrastructure and engineering needed to deploy, scale, and operationalize the analytics program.

​Required Qualifications and Technical Skills

​The position requires senior-level experience, strong analytical skills, and proficiency in the tools necessary for modern data-driven fraud detection.

• ​Experience: 10+ years of relevant experience in data analytics, with seasoning in Fraud/Identity operations.
• ​Technical Tools: Experience with SQL, Python, and analytics tools.
• ​Visualization: Skilled in data visualization and enabling dynamic dashboards in Tableau.
• ​Database Knowledge: Experience with both relational and non-relational database systems and database architecture.
• ​Soft Skills: Ability to work autonomously, deliver high-quality work, and succinctly articulate complex ideas and explain technical decisions to both technical and non-technical audiences.