Model Risk Manager

This is a fully remote position, open to applicants in United States, +4 more locations.

📋 Description

• Conduct independent validations and assessments of both internally created and third-party models related to credit, fraud, BSA/AML, CECL, finance, liquidity, pricing, and operational risk.

• Analyze model methodology, assumptions, data quality and lineage, implementation, and performance through outcomes analysis, benchmarking, back-testing, and sensitivity testing.

• Offer credible and constructive challenges to model developers, owners, and users.

• Evaluate model risk and significance based on inherent risk, purpose, exposure, usage, and potential impact.

• Maintain a comprehensive and accurate model inventory, detailing ownership, risk rating, dependencies, limitations, validation status, monitoring requirements, and unresolved issues.

• Review ongoing monitoring plans and results, including performance thresholds, overrides, data drift, model adjustments, and suitability for purpose.

• Assess vendor models and third-party analytical products.

• Document validation findings, identify issues, propose remediation, and track findings until resolution.

• Support controlled model usage when validation cannot be finalized prior to implementation.

• Create reports on model risk, validation coverage, performance issues, concentrations, dependencies, exceptions, and overdue remediation.

• Enhance Mercury’s Model Risk Management Policy, standards, procedures, and templates.

• Utilize automation and analytical tools to refine model inventory management, testing, monitoring, and reporting.

• Collaborate with Data and AI Governance teams regarding the intersection of traditional model risk management and generative AI, agentic AI, and other analytical systems.

• Assist with regulatory examinations, Internal Audit reviews, and other assurance activities related to model risk.

⛳️ Requirements

• A minimum of 5 years of relevant experience in model validation, model development, quantitative risk analytics, or a related field within banking, fintech, financial services, or consulting.

• Bachelor's degree in Statistics, Mathematics, Physics, Computer Science, Engineering, Financial Engineering, or a related discipline.

• Extensive knowledge of model risk management principles and current regulatory expectations, including the updated interagency guidance outlined in SR 26-2.

• Significant experience validating or developing models in areas such as BSA/AML, fraud, financial forecasting, CECL, capital, liquidity, and credit underwriting.

• Familiarity with machine learning methodologies such as XGBoost and random forests, scorecards, complex vendor models, and intricate spreadsheet-based models.

• Proficient in SQL and Python.

• Strong written and verbal communication abilities.

• Exceptional attention to detail in documentation, code base, testing artifacts, and quantitative analysis.

• Sound judgment and a pragmatic, risk-based mindset.

• High ownership, intellectual curiosity, and comfort in establishing processes within a rapidly evolving environment.

• A master's degree or PhD is preferred.

• Experience in developing or significantly enhancing a model risk management program is preferred.

• Familiarity with bank regulatory examinations, charter readiness, or implementing risk programs within a growing financial institution is preferred.

• Knowledge of Haskell is preferred.

🏝️ Benefits

• Base salary.

• Equity (stock options/RSUs).

• Benefits.

• Equal Employment Opportunity employer.

• Reasonable accommodations throughout the recruitment process for applicants with disabilities or special needs.