Advanced Fraud Detection and Typology Analyst

Senior data analyst in Fraud Prevention and Detection focusing on identifying emerging fraud typologies and anomalous patterns across the Specialized Consumer Client Solutions line. Leverages exploratory, hypothesis-driven analytics on large, complex datasets to surface novel fraud risks, understand attacker behavior, and inform detection strategies. Executes long-term strategic initiatives, manages complex projects from initiation to delivery, and partners with Fraud Strategy, GIS, Client Protection, Digital and Technology teams to translate analytical insights into actionable detection rules, models, and investigations prioritization. Core capabilities include pattern recognition, clustering, anomaly detection, networked behavior analysis, data storytelling, and producing executive-ready visualizations and narratives to communicate findings. Requirements include demonstrated experience identifying evolving fraud behaviors, strong SQL proficiency, at least one analytics language (Python/SAS), and 2+ years in fraud, risk, cyber, or financial services analytics. Preferred education includes a Bachelor’s degree in a quantitative field or equivalent practical experience; advanced degrees and experience with graph-based/fraud-detection use cases are desirable. The role emphasizes independent work with ambiguity, rigorous analytical judgment, and the ability to influence senior leaders without direct authority.