The Senior Fraud Data Analyst will lead efforts in fraud prevention and detection using data-driven strategies. This role requires analyzing transactional data, developing fraud models with machine learning tools, and collaborating across departments to mitigate financial risks. Responsibilities include root cause analysis of fraudulent incidents, creating analytics dashboards for performance tracking, and ensuring compliance with regulatory standards.

Bachelor's degree in data analytics, statistics, or related field required. Master's or PhD preferred. Experience in fraud prevention within financial services industry. Advanced skills in Python, SQL, Power BI, Tableau, and machine learning techniques. Familiarity with SIEM tools like Splunk or ArcSight. Strong analytical and problem-solving abilities to identify and mitigate fraud patterns.