Manager, Fraud Analytics & Governance

Manager, Fraud Analytics & Governance

Onsite 3 days each week in either New York City, Chicago, Jacksonville, FL or Sioux Falls.

Candidates need to work 3 days onsite each week in either New York City or Chicago.

Role Summary

As a key member of the Fraud Analytics, Modeling & Intelligence organization, you will design and execute data-driven fraud strategies for North American and global portfolios. This high-impact role focuses on the full fraud lifecycle-from preventing synthetic ID and application fraud to mitigating sophisticated account takeover (ATO) schemes. You will sit at the intersection of data science and risk management, leveraging large-scale datasets to build proactive defenses that safeguard our customers and the bank's reputation.

Key Responsibilities include:

Strategy & Execution:

Lead Fraud Strategy: Design, test, and implement automated fraud risk strategies within advanced decision engines for consumer and commercial portfolios.

Lifecycle Management: Manage the end-to-end model lifecycle, partnering with developers, vendors, and Model Risk Management (MRM) to ensure models are validated, high-performing, and compliant.

Innovation: Continuously evaluate new data sources, AI/ML capabilities, and external tools to stay ahead of evolving fraud patterns.

Analytics & Insights:

Advanced Data Mining: Extract actionable insights from Big Data environments (Hadoop, Hive, Python) to identify emerging attack vectors and behavioral trends.

Reporting & Governance: Support the "Authorization Governance" process by monitoring historical performance and translating complex data into clear, executive-level documentation.

Technical Documentation: Produce rigorous technical reports that meet regulatory standards and survive deep-dive audits from supervisory authorities.

Collaboration & Leadership:

Cross-Functional Partnership: Act as a critical liaison between Fraud Policy, Operations, and Technology to ensure seamless execution of business priorities.

Risk Advocacy: Foster a culture of transparency and ethical judgment, ensuring all strategic decisions align with global compliance and regulatory requirements.

Qualifications:

Experience: 5+ years in Fraud, Payments, or Risk Analytics. Experience in the banking or fintech sector is highly preferred.

Technical Proficiency: 3+ years of hands-on experience in a Big Data environment. Advanced proficiency in Python, SQL, SAS, or Hive/Impala is required.

Analytical Rigor: Proven ability to apply mathematical and statistical techniques to solve complex, real-world business problems.

Communication: Exceptional ability to "translate" technical findings into strategic narratives for senior leadership and regulatory bodies.

Autonomy: A self-starter capable of navigating a complex global matrix organization with minimal oversight.

Education:

Required: Bachelor's Degree in a quantitative field (Statistics, Mathematics, Physics, Economics, or Computer Science).

Preferred: Master's Degree or Ph.D. in a related field.

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