Manager, Model Risk Management

The Clearing House•Grace NY Office, NY

2d•$120,000 - $155,000•Hybrid

About The Position

The Manager, Model Risk Management plays a central leadership role in overseeing enterprise-wide model risk activities across all phases of the model lifecycle. This position expands beyond day-to-day analytical responsibilities to include governance ownership, cross-functional collaborations, vendor model oversight, and enhanced subject-matter expertise in AI/ML and Generative AI (GenAI) model risks. The Manager will ensure strong regulatory alignment, transparent reporting, and effective risk mitigation practices for operational, analytical, financial and AI-driven models used across the organization.

Requirements

Bachelor’s degree in mathematics, statistics, finance, computer science, data science, engineering, or related quantitative field; Master’s, MBA, or Doctorate preferred.
7–10 years of experience in model risk management, model validation, quantitative analytics, model or AI/ML development, risk governance, or equivalent.
Strong understanding of model lifecycle governance, regulatory expectations (The Fed), and industry model risk frameworks.
Hands-on experience assessing or validating traditional models as well as AI/ML or GenAI models.
Knowledge of model explainability tools, AI ethics, and responsible AI principles.
Ability to interpret, challenge, and communicate complex modeling concepts to both technical and non-technical audiences.
Ability to work collaboratively with others to build strong relationships across the organization.
Proficiency in analytical tools such as Python or R; strong Excel and dashboarding skills (e.g., Tableau).
Excellent written and verbal communication skills, including experience preparing committee-level reporting

Nice To Haves

Experience reviewing or overseeing vendor-provided models and third-party risk documentation, a plus
Familiarity with model risk supervision within financial services, payments, or clearinghouse environments.
Knowledge of model explainability tools, AI ethics, and responsible AI principles.
Experience mentoring or supervising analysts or junior staff.

Responsibilities

Oversees model risk governance across all business units to ensure alignment with the current Model Risk framework.
Maintains and updates Model Risk Management Framework, and policies as required by industry changes.
Advise model developers and business units on model expectations.
Conduct independent validation activities covering conceptual soundness, methodology, performance testing, data quality, sensitivity/benchmark analysis, and outcomes analysis.
Prepare comprehensive validation documents including evidence of validation activities supporting final recommendations.
Supervise more complex reviews of AI/ML and GenAI systems, including robustness testing, explainability assessment, hallucination/response integrity evaluation, drift analysis, and model fairness or bias testing.
Review and challenge validation work performed by peers or third-parties; provide prescriptive feedback and ensure consistency and quality across deliverables.
Lead governance activities for the full model lifecycle—including identification, risk rating, validation, approval, monitoring, periodic review, change management, and retirement—ensuring compliance with internal policies and regulatory expectations.
Monitor findings and remediations related to Model Validations.
Maintain enterprise model inventory and ensure documentation quality, completeness, and audit readiness for all models.
Assess and approve model monitoring submissions.
Contribute to the enhancement and implementation of the Model Risk Management (MRM) frameworks, processes, and standards.
Collaborate with cross-functional stakeholders to ensure model risks are appropriately governed and mitigated.