Risk Specialist I, Vendor Investigations & Transaction Accuracy, VITA

Amazon is seeking a data-driven, detail-oriented Risk Specialist I to join Vendor Investigations & Transaction Accuracy's (VITA) Digital Fraud team. This team is responsible for detecting, preventing, and investigating fraudulent vendor activity across Amazon's digital businesses, leveraging advanced fraud detection technologies including graph-based data clustering, machine learning risk models, and real-time payment screening rules to identify fraudulent vendor accounts and stop erroneous payments before they occur. As an investigator on this team, you will review cases surfaced by these detection systems, validate connections between accounts under review and known fraud actors, make decisions on vendor accounts, and contribute to the continuous improvement of our detection capabilities. A successful candidate is analytically rigorous, comfortable navigating complex and ambiguous datasets, and thrives in a fast-paced environment where fraud patterns evolve continuously. You must be passionate about protecting Amazon's financial integrity while maintaining the highest standards of controllership, and eager to contribute ideas that enhance our detection and investigation processes. Key job responsibilities • Investigate cases of suspected vendor fraud across digital programs, analyzing graph-based clustering outputs, risk signals and data patterns to validate or disprove fraud linkages to make timely, well-supported decisions • Query and analyze large datasets using SQL and visualization tools (e.g., Power BI, QuickSight) to identify fraud patterns, validate detection outputs, and support investigative deep dives • Identify emerging fraud schemes and modus operandi, provide feedback on detection rule performance (true positive/false positive rates), and escalate patterns for systemic automation resolution • Support the development and tuning of fraud detection models, including contributing to AI/ML-assisted detection workflows through investigator feedback and data labeling • Document investigation findings with clear rationale, preserve evidence and communicate root causes and recommendations to management and cross-functional stakeholders • Contribute to building and updating SOPs, propose process improvements that increase efficiency or detection accuracy, and maintain productivity targets within defined SLAs • Coordinate with technology teams, business partners, and Finance Operations on fraud mitigation efforts and support reporting on program metrics (loss avoidance, rejection rates, detection volumes)