VP AI Model Validation

Come work with us:

Metropolitan Commercial Bank (the "Bank") is a full-service commercial bank based in New York City. The Bank provides a broad range of business, commercial, and personal banking products and services to individuals, small businesses, private and public middle-market and corporate enterprises and institutions, municipalities, and local government entities.

Metropolitan Commercial Bank was named one of Newsweek's Best Regional Banks and Credit Unions 2024. The Bank was ranked by Independent Community Bankers of America among the top ten successful loan producers for 2023 by loan category and asset size for commercial banks with more than $1 billion in assets. Kroll affirmed a BBB+ (investment grade) deposit rating on January 25, 2024.

For the fourth time, MCB has earned a place in the Piper Sandler Bank Sm-All Stars Class of 2024.

Metropolitan Commercial Bank operates banking centers and private client offices in Manhattan, Boro Park, Brooklyn and Great Neck on Long Island in New York State.

The Bank is a New York State chartered commercial bank, a member of the Federal Reserve System and the Federal Deposit Insurance Corporation, and an equal housing lender. The parent company of Metropolitan Commercial Bank is Metropolitan Bank Holding Corp. (NYSE: MCB).

Position Summary:

The Vice President AI Model Validation with extensive big-bank experience, strong technical expertise, and proven capabilities in model risk management, risk reporting, and large-scale data management, will be responsible for developing, maintaining, and enhancing the Bank's Model Risk Management framework in compliance with regulatory guidance (e.g., SR 11-7). This individual will be well-versed in regulatory requirements, model governance frameworks, and secure data practices, enabling a more resilient, compliant, and value-added risk management function.

The VP AI Model Validation will oversee the governance, validation, monitoring, and reporting of models used across the Bank-including BSA/AML, Credit, CECL, ALM, Capital planning, Stress testing, liquidity, and other decision-support models.

The ideal candidate will combine strong quantitative skills with practical banking experience, expertise in data quality and visualization, and the ability to clearly communicate technical model risk findings to senior management, regulators, and business stakeholders. The knowledge and ability to conduct thorough model validations and reviews is a critical responsibility for this position.

The successful candidate for this role will be a proactive and analytical individual with a solid understanding of risk management principles, excellent communication skills, and the ability to work collaboratively in a dynamic environment. This role reports to the Director of Model Risk & Risk Reporting and will be based in New York City.

We have a flexible work schedule where employees can work from home one day a week.

Essential duties and responsibilities:

Governance and Policy Compliance:

• Support and enhance the Bank's Model Risk Management policy, procedures, and control framework.
• Maintain a comprehensive model inventory, ensuring accuracy, completeness, and appropriate model tiering.
• Oversee and lead model lifecycle governance, including development, implementation, use, monitoring, and retirement.
• Ensure full compliance with SR 11-7, CECL, and other regulatory guidance.

Model Validation & Review

• Conduct independent validations of models, including BSA/AML, CECL/ALLL, Credit, ALM, stress testing, market risk, and liquidity models.
• Assess conceptual soundness, input data integrity, methodology, and performance monitoring.
• Challenge assumptions, limitations, and use cases of models, and provide recommendations for remediation.
• Document validation results and present findings to senior management, committees, and regulators.

Data Governance & Reporting

• Design and implement data quality processes to support reliable model inputs and outputs, and data used across MRM reporting.
• Establish controls for data accuracy, completeness, timeliness, and reconciliation across model datasets.
• Develop Power BI dashboards and automated reports to track model performance, issues, and usage.
• Support regulatory and management reporting through clear, visual, and actionable insights.

Monitoring & Issue Management

• Execute ongoing model performance monitoring plans, including back-testing and benchmarking.
• Track and manage model risk issues, findings, and remediation efforts.
• Provide regular reporting on model risk metrics, emerging trends, and validation progress.

Stakeholder Engagement

• Partner with business units, finance, risk, audit, and IT to ensure models meet business and regulatory needs.
• Provide training and guidance to model owners and users on governance and data quality requirements.
• Support Internal Audit and regulatory examinations related to model risk.

Continuous Improvement:

• Continuously review and enhance risk management processes, tools, and methodologies to adapt to…