The Model Risk Management Group (MRMG) is seeking a highly motivated analyst to support independent validation and governance of Finance & Treasury models, including CCAR PPNR models, Membership Rewards URR models, Moody's macroeconomic models, and related Non-Model Tools.
The role provides an opportunity to work closely with model developers, business partners, and senior risk leaders to ensure models and tools are conceptually sound, analytically robust, and compliant with internal governance standards and regulatory expectations. The successful candidate will contribute to strengthening model risk management practices while gaining exposure to regulatory capital planning, financial forecasting, and enterprise risk management.
- Support independent validation of Finance & Treasury models, including CCAR PPNR, Membership Rewards URR, Moody's macroeconomic models, and Non-Model Tools.
- Review model methodology, assumptions, data, implementation, and performance to assess conceptual soundness and ongoing suitability.
- Perform independent analytical testing, benchmarking, sensitivity analysis, and replication to effectively challenge first-line model development teams.
- Evaluate model documentation and governance against internal standards and regulatory expectations, identifying gaps and recommending improvements where appropriate.
- Track validation findings and support review of remediation evidence to ensure timely and sustainable closure.
- Prepare clear, concise validation reports and communicate findings to model developers, stakeholders, and senior leadership.
- Partner with cross-functional teams to support regulatory exams, internal audits, annual reviews, model changes, and special governance initiatives.
- Contribute to research and continuous improvement initiatives that enhance validation methodologies, analytical techniques, and governance processes.
- Bachelor's or Master's degree in Statistics, Mathematics, Economics, Finance, Engineering, Computer Science, Operations Research, or a related quantitative discipline.
- Strong analytical and problem-solving skills with the ability to interpret quantitative results and communicate insights effectively.
- Experience with Python, SQL, SAS, R, or similar analytical tools.
- Understanding of statistical modeling, forecasting techniques, regression analysis, or machine learning fundamentals.
- Excellent written and verbal communication skills.
- Ability to manage multiple priorities while delivering high-quality work in a collaborative environment.
- Experience in model development, model validation, model risk management, or quantitative analytics within financial services.
- Familiarity with CCAR, CECL, IFRS 9, stress testing, regulatory capital planning, or financial forecasting models.
- Knowledge of model governance, validation methodologies, and regulatory guidance (e.g., SR 11-7).
- Experience working with large datasets and applying statistical techniques to solve business problems.
- Demonstrated ability to exercise independent judgment while building strong partnerships across business and risk functions.