Model and Data Manager - Fraud Department - Vice President

What You'll Do In The Role

• Data Onboarding: Working with Fraud Leadership and technology partners, identify and onboard new and ongoing data sources as required to satisfy Fraud data needs to support ongoing Fraud efforts, and enable Fraud coverage of new products and capability launches for the Firm.
• Model Onboarding: Oversee the end-to-end onboarding process for new internally developed and vendor supplied models, updated fraud models, including coordination with data science, technology, and business teams. Ensure all models meet regulatory and internal standards prior to deployment.
• Model Monitoring: Lead the ongoing performance monitoring of all fraud models, including periodic validation, back-testing, and performance reporting. Identify model drift, degradation, or emerging risks and coordinate timely remediation.
• Collaboration with Model Risk Management: Serve as the primary point of contact with the Model Risk Management function. Facilitate model validation, inventory management, control testing, and documentation updates to meet organizational and regulatory requirements. Ensure documentation covers assumptions, limitations, risk controls, data lineage, and governance touchpoints.
• Governance and Compliance: Govern the end-to-end model life cycle including development, validation, implementation, change management, monitoring, and decommissioning, ensuring robust controls at each stage. Ensure adherence to all internal model governance policies and external regulatory guidelines.
• Prepare and present model performance and risk assessments to senior management and governance committees.
• Stakeholder Engagement: Work cross-functionally with fraud operations, analytics, IT, compliance, and audit teams to ensure model integrity, transparency, and accountability.
• Team Leadership: Lead, mentor, and develop a team of fraud model analysts and specialists. Foster a culture of innovation, collaboration, and continuous learning.
• Innovation: Assess and guide the adoption of innovative modeling techniques (e.g., AI/ML) within the governance framework. Stay abreast of emerging risks, new fraud typologies, evolving regulatory expectations, and best practices in model risk for financial crimes and fraud detection.

What You'll Bring To The Role

• Bachelor’s or Master’s degree in quantitative field (e.g., Statistics, Mathematics, Data Science, Engineering, or related discipline).
• 10+ years of experience in fraud risk management, model risk management, or related analytical functions within the financial services industry.
• Strong expertise in model development, validation, and governance processes.
• Demonstrated experience leading cross-functional teams and managing complex projects.
• Excellent communication, stakeholder management, and presentation skills.
• In-depth knowledge of regulatory requirements related to model risk (e.g., SR 11-7, OCC 2011-12) is highly desirable.

Preferred Skills

• Proficiency in data analytics tools and programming languages (e.g., Python, R, PySpark, etc.).
• Demonstrated experience with advanced fraud detection technologies, such as machine learning and artificial intelligence.
• Able to manage competing priorities in a fast-paced environment.