Fraud Analytics & Strategy Manager [AQ-15190]

About the role

The Fraud Analytics & Strategy Manager position requires a hybrid schedule in one of the following locations: Dallas/Irving (TX), New Castle (DE), Jacksonville (FL), Sioux Falls (SD).

Responsibilities

• Design, test, and implement robust fraud mitigation rules and authorization governance strategies across decisioning systems.
• Leverage advanced analytics to detect emerging trends, optimize decision engines, and mitigate attacks across the full fraud lifecycle.
• Act as a critical bridge between data, strategy, policy, and model risk management to safeguard the firm and its customers.
• Strategy & Decision Engine Optimization: Design, test, and implement robust fraud mitigation rules and authorization governance strategies across decisioning systems, adhering to strict change-control standards.
• Model Risk Management & Lifecycle Oversight: Serve as a primary lead for Fraud Model Risk—partnering with modelers, external vendors, and internal validators across the model lifecycle.
• Advanced Data Analytics & Trend Detection: Query large-scale datasets using SAS, SQL, or open-source tools to identify behavioral patterns, assess rule performance, and translate raw data into actionable insights for executive leadership.
• Regulatory Compliance & Technical Documentation: Package comprehensive analysis into technical documentation that meets regulatory guidelines and industry standards.
• Present model validation findings to senior management and supervisory authorities as required.
• Cross-Functional Leadership: Partner closely with Fraud Policy, Operations, Product, and IT teams to align fraud strategies with business growth, technology roadmaps, and incident management protocols.
• Continuous Innovation: Research and evaluate new data sources, analytical tools, and technology capabilities to continuously enhance our fraud detection architecture and process efficiencies.

Qualifications & Skills

• Education: Bachelor’s degree in a quantitative discipline (Statistics, Mathematics, Economics, Data Science, or related field).
• Experience: 5+ years in fraud strategy, quantitative analytics, or risk management within financial services.
• Technical Background: Intermediate to advanced proficiency in SAS or SQL for complex data manipulation, strategy monitoring, and performance assessments; strong hands-on proficiency in Excel for data modeling and reporting; experience working within Big Data environments (e.g., Python, Hive, Impala) and performing mathematical/statistical analysis on large datasets; demonstrated familiarity with model development, production deployment, and model risk governance frameworks.
• Communication & Influence: Proven ability to translate complex analytical findings into executive-ready presentations and interface confidently with regulatory auditors and senior leaders.

Preferred Qualifications (Strong Plus)

• Master’s Degree in a quantitative or technical field.
• Domain Expertise: 2+ years of direct experience in the payments industry, particularly with credit card products, payment rails, Mastercard ecosystems, and associated fraud vectors.
• Project Management: Track record of driving cross-functional initiatives and managing system incident responses in a fast-paced environment.