Manager, Fraud Detection and Analytics

Responsibilities

• Analyze complex datasets to identify risk signals related to fraudulent debit card transactions.
• Use Python, SQL, and analytical tools to analyze large, complex datasets and extract actionable insights.
• Implement fraud detection strategies in a real-time fraud decisioning engine.
• Support anomaly detection efforts to identify coordinated fraud attacks and organized fraud rings.
• Communicate insights clearly and effectively to influence stakeholders and drive product changes.
• Collaborate across business units to drive data-informed strategies for fraud detection.
• Contribute to the continuous improvement of the fraud detection program, through rule and model refinement, fraud hunting, and data discovery.

• Bachelor's with 5 plus years or Master's with 3 plus years of experience in data analytics, preferably in fraud detection, cybersecurity, or risk domains.
• Strong proficiency in Python and SQL for data analysis and automation.
• Experience working with large-scale datasets and analytical platforms.
• Skilled in using analytics tools (e.g., dashboards, statistical packages, data visualization platforms) to perform advanced analytics and uncover actionable insights.
• Familiarity with payment card fraud detection and risk management.
• Ability to translate complex data into clear, actionable insights.
• Strong communication and collaboration skills to work across teams and influence decisions.
• Experience in anomaly detection or fraud analytics is a plus.

• Python
• SQL
• data analysis
• fraud detection
• anomaly detection
• data visualization
• statistical analysis
• data automation
• rule refinement
• model refinement

• communication
• collaboration
• influencing
• data interpretation
• problem-solving
• stakeholder engagement
• strategic thinking
• analytical thinking
• teamwork
• adaptability