Fraud Analytics & Strategy Manager [AQ-16527]

About the role

This is an exciting opportunity to join a critical team at the heart of our partner's defense against fraud. In this pivotal role, you will design, execute, and scale sophisticated, data-driven fraud strategies that protect diverse financial portfolios and products. You will play a key role in detecting emerging trends, optimizing decision engines, and mitigating attacks across the full fraud lifecycle, from synthetic identity fraud to account takeover and complex new attack vectors. This position serves as a critical bridge, translating data into actionable insights that safeguard the firm and its customers, making a tangible impact on global financial security.

Responsibilities

• Design, test, and implement robust fraud mitigation rules and authorization governance strategies across decisioning systems, adhering to strict change-control standards.
• Serve as a primary lead for Model Risk, partnering with modelers, external vendors, and internal validators across the model lifecycle (validation, ongoing performance monitoring, versioning, and annual reviews).
• 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.
• 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.
• Partner closely with Policy, Operations, Product, and IT teams to align fraud strategies with business growth, technology roadmaps, and incident management protocols.
• Research and evaluate new data sources, analytical tools, and technology capabilities to continuously enhance fraud detection architecture and process efficiencies.

Qualifications

• Bachelor's degree in a quantitative discipline (Statistics, Mathematics, Economics, Data Science, or related field).
• 5+ years of experience in fraud strategy, quantitative analytics, or risk management within financial services.
• 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.
• Proven ability to translate complex analytical findings into executive-ready presentations and interface confidently with regulatory auditors and senior leaders.

Nice-to-Have Qualifications

• Master's Degree in a quantitative or technical field.
• 2+ years of direct experience in the payments industry, particularly with payment systems and associated fraud vectors.
• Track record of driving cross-functional initiatives and managing system incident responses in a fast-paced environment.