Risk and Central Monitoring Associate Manager overseeing RBQM and central monitoring for Worldwide Clinical Trials, a global clinical research organization. Supporting risk assessments, KRIs, QTLs, dashboards, and inspection readiness.
About the role
- Model Risk Manager validating financial models and strengthening Mercury’s fintech risk governance. Partnering across Risk, Data, Engineering, Product, Finance, Compliance, and Audit.
Responsibilities
- Perform independent validations and reviews of internally developed and third-party models across credit, fraud, BSA/AML, CECL, finance, liquidity, pricing, and operational risk
- Evaluate model methodology, assumptions, data quality and lineage, implementation, and performance through outcomes analysis, benchmarking, back-testing, and sensitivity testing
- Provide credible and constructive challenges to model developers, owners, and users
- Assess model risk and materiality based on inherent risk, purpose, exposure, use, and potential impact
- Maintain a complete and accurate model inventory, including ownership, risk rating, dependencies, limitations, validation status, monitoring requirements, and open issues
- Review ongoing monitoring plans and results, including performance thresholds, overrides, data drift, model changes, and fitness for purpose
- Evaluate vendor models and third-party analytical products
- Document validation conclusions, identify issues, recommend remediation, and track findings through resolution
- Support controlled model use when validation cannot be completed before implementation
- Develop reporting on model risk, validation coverage, performance concerns, concentrations, dependencies, exceptions, and overdue remediation
- Improve Mercury’s Model Risk Management Policy, standards, procedures, and templates
- Use automation and analytical tools to improve model inventory management, testing, monitoring, and reporting
- Partner with Data and AI Governance teams on boundaries between traditional model risk management and generative AI, agentic AI, and other analytical systems
- Support regulatory examinations, Internal Audit reviews, and other assurance activities involving model risk
Requirements
- 5+ years of relevant experience in model validation, model development, quantitative risk analytics, or a related discipline within banking, fintech, financial services, or consulting
- Bachelor’s degree in Statistics, Mathematics, Physics, Computer Science, Engineering, Financial Engineering or a related field
- Strong knowledge of model risk management principles and current regulatory expectations, including the revised interagency guidance reflected in SR 26-2
- Intensive experience validating or developing models in areas such as BSA/AML, fraud, financial forecasting, CECL, capital, liquidity, and credit underwriting
- Experience with machine learning methodologies such as XGBoost and random forests, scorecards, complex vendor models, and complex spreadsheet-based models
- Proficiency with SQL and Python
- Strong written and verbal communication skills
- Exceptional attention to detail across documentation, code base, testing artifacts and quantitative analysis
- Sound judgment and a practical, risk-based mindset
- High ownership, intellectual curiosity, and comfort building processes in a fast evolving environment
- Master’s degree or PhD is preferred
- Experience helping build or materially enhance a model risk management program is preferred
- Familiarity with bank regulatory examinations, charter readiness, or implementation of 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
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