Model Risk Manager - Iselin, NJ

How would you like to join one of the most highly regarded financial institutions in New Jersey with deep roots in the community? Provident is a successful and highly regarded multi-billion-dollar bank that continues to grow with branches in New Jersey, Eastern Pennsylvania and New York. Our longevity is a testament to our commitment to placing our employees, customers and the communities we serve at the center of all we do. At Provident Bank, we are committed to enhancing our customer and employee experience.

POSITION OVERVIEW

Reporting to the Chief Risk Officer, the Model Risk Manager serves as the Bank's independent second-line authority for Model Risk Management (MRM). This position provides effective challenge and oversight of the Bank's use of models, quantitative methods, analytical tools, and other model-driven decision-support systems. The Model Risk Manager maintains and continuously enhances the Bank's Model Risk Management Framework to align with regulatory expectations and industry practices.

The position oversees the full model lifecycle, including model identification, inventory management, risk tiering, validation, implementation oversight, performance monitoring, change management, and retirement. The role performs and oversees independent model validations, manages third-party validation providers, challenges model owners and business lines, and reports model risk exposures and emerging concerns to management and governance committees.

The Model Risk Manager also supports oversight of data dependencies affecting model outputs and helps the Bank assess risks associated with artificial intelligence, machine learning, advanced analytics, and evolving decision-support technologies.

KEY RESPONSIBILITIES

Model Risk Management Program Leadership

• Maintain and continuously enhance the Bank's MRM Framework, including model governance policies, standards, procedures, methodologies, and reporting.
• Serve as the independent second-line subject matter expert on model risk management across the Company.
• Provide effective challenge regarding model design, assumptions, limitations, implementation, data quality, performance, and use.
• Maintain the enterprise model inventory and model risk classification methodology, ensuring complete and accurate identification and risk tiering of models.
• Oversee governance of quantitative models used for credit risk, CECL, capital planning, liquidity risk management, asset liability management, stress testing, fraud monitoring, marketing analytics, pricing, forecasting, and other business purposes.

Model Validation and Independent Review

• Perform independent validations and periodic model reviews using regulatory guidance and industry-accepted validation methodologies.
• Manage third-party validation providers, including engagement oversight, quality review, challenge of conclusions, and issue remediation.
• Evaluate conceptual soundness, methodology, data integrity, implementation accuracy, process controls, assumptions, limitations, outcomes analysis, benchmarking, sensitivity testing, stress testing, and back-testing.
• Assess model findings, limitations, and compensating controls, and ensure appropriate remediation plans are developed and monitored through completion.
• Present validation results and recommendations to management committees, senior management, Audit, and regulators.

Model Lifecycle Oversight

• Oversee governance throughout the full model lifecycle, including development, acquisition, implementation, use, monitoring, change management, redevelopment, decommissioning, and retirement.
• Review proposed model changes and determine validation requirements and risk implications.
• Monitor model performance and usage trends to identify deterioration, emerging risk, control weaknesses, or changing business conditions affecting model reliability.

Third-Party, Vendor, and Analytical Tool Governance

• Oversee governance and risk assessment activities for vendor-developed models, externally sourced methodologies, and significant analytical tools used in business decision-making.
• Evaluate model documentation, vendor assumptions, implementation controls, performance-monitoring practices, and independent-review requirements.
• Ensure suitable oversight for critical tools that may not meet the regulatory definition of a model but require enhanced governance because of their significance to decision-making.

Governance and Reporting

• Serve as Chairperson of the Model Risk Management Committee.
• Develop and present periodic reporting on model inventory status, validation activity, findings, remediation efforts, emerging model risks, and program effectiveness.
• Coordinate interactions with regulators, Internal Audit, external auditors, and consultants regarding model risk management matters.
• Monitor regulatory developments and emerging industry practices and recommend appropriate enhancements to the Bank's MRM program.

Data Governance and Model Data Oversight

• Assist in developing and executing second-line oversight activities related to data governance, data quality, and data controls supporting the Bank's models.
• Assess the completeness, accuracy, lineage, governance, and control environment surrounding model inputs and outputs.
• Review data sourcing, transformations, reconciliations, and key assumptions supporting critical models.
• Collaborate with business units, Technology, and governance functions to identify and remediate data-related risks affecting model reliability and decision-making.
• Support enterprise initiatives involving data governance, model data quality, and analytical risk management.

Artificial Intelligence, Advanced Analytics, and Emerging Technologies

• Oversee second-line governance and independent review of artificial intelligence, machine learning, generative AI, predictive analytics, and other advanced analytical solutions used by the Bank.
• Assess governance, validation, testing, monitoring, transparency, explainability, data quality, bias assessment, and outcome validation supporting AI-enabled solutions.
• Support the development and maintenance of enterprise standards governing the acquisition, deployment, monitoring, and retirement of AI-enabled technologies.
• Coordinate with Information Security, Data Governance, Compliance, Legal, Operational Risk, and business-line partners to apply appropriate risk practices throughout the lifecycle of AI-enabled solutions.

MINIMUM QUALIFICATIONS

• 5-7 years of professional experience involving quantitative analysis, statistical modeling, model validation, model governance, or model risk management.
• At least 3 years of experience within financial services, banking, consulting, regulatory, audit, or risk management environments involving quantitative model oversight.
• Financial-industry experience in model risk management or the use of models, with sufficient quantitative and technical experience to perform validations.
• Strong knowledge of SR 11-7 and OCC and FDIC supervisory expectations relating to model risk management.
• Understanding of statistical modeling, quantitative analytics, machine learning concepts, forecasting methodologies, and risk measurement techniques.
• Experience performing or overseeing independent model validations.
• Familiarity with CECL, ALM, liquidity, capital planning, stress testing, fraud analytics, and other banking-focused quantitative models.
• Demonstrated ability to independently challenge model developers, business-line management, vendors, and third parties.
• Knowledge of data governance, data lineage, data-quality management, and control frameworks supporting model risk management.
• Excellent written and verbal communication skills, including the ability to present highly technical concepts to executive management, committees, auditors, and regulators.
• No current direct supervisory responsibility. The role oversees third-party staff supporting model validation and may supervise staff if validations transition in-house.

PREFERRED QUALIFICATIONS

• Degree or concentration in a quantitative field such as mathematics, physics, engineering, computer science, or financial engineering.
• Experience interacting with senior management, regulators, auditors, or governance committees.
• Experience managing third-party validation providers and model-remediation efforts.
• Risk-management-related certification or a principles-based certification demonstrating mastery of a relevant framework or methodology.

WORKING CONDITIONS

• Work is performed in a normal office environment. Noise levels are usually moderate.
• Prolonged sitting.
• Lifting from 5 to 10 lbs. (printer paper, storage boxes).
• Occasional bending or overhead lifting (storing files or boxes).
• Hazards are primarily those present in a normal office setting.

PAY AND BENEFITS

Pay Details: $142,000 - $163,300 annually

Please note: The base pay actually offered may vary based on the candidate's skills and experience, job-related knowledge, education, geographic location, internal equity, and other applicable business and organizational needs.

This role is incentive eligible based on company, business, and/or individual goal achievement and performance.

Team members accrue Paid Time Off (PTO), receive paid holidays, and are eligible to participate in the Bank's Health and Wellness benefits, including Medical, Dental, and Vision Plans, Flexible Spending Accounts (FSA), Health Savings Accounts (HSA), and a 401(k) Retirement Plan. Additional benefits include Disability Insurance, an Employee Assistance Program (EAP), and Basic Life Insurance. Company-sponsored Tuition Disbursement and Loan Repayment programs are also available. Voluntary benefits include Supplemental Life Insurance, Accident, Critical Illness, Hospital Indemnity, and Legal plans.

ADDITIONAL INFORMATION

This job description may not be all-inclusive. Employees are expected to perform other duties as assigned and directed by management. Job descriptions and duties may be modified when deemed appropriate by management.

Provident Bank recognizes and supports the importance of creating a socially and culturally diverse employee base. We understand, value, and appreciate the unique perspectives that a diverse workforce can contribute to our organization. We put the employee and the customer at the center of strategy because culture is a critical differentiator for why people choose to work here.

We are an equal opportunity employer, and all qualified applicants will receive consideration for employment without regard to age 40 and over, color, disability, gender identity, genetic information, military or veteran status, national origin, race, religion, sex, sexual orientation, or any other applicable status protected by state or local law.