PenFed is looking to solve the problem of ensuring the integrity, compliance, and effectiveness of quantitative risk models, specifically AI/ML models, across the enterprise by establishing a robust Model Risk Management (MRM) function.
Requirements
- Proficiency in AI/ML methods, NLP, LLM, GenAI, statistical modeling and model validation techniques, including model implementation validation & testing.
- Minimum of five (5) years’ experience with programming tools, including SAS, Python, or R, required.
- Minimum five (5) years’ experience in AI/ML models is required.
- Demonstrated knowledge of model risk management and associated regulatory requirements (FRB SR11-7, SR 15-18, and SR 16-11).
- Extensive experience in model development or model risk management with the financial service industry.
- Experience in governance or second-line roles.
- Experience working with regulators on model validation processes.
Responsibilities
- Contributes to development and governance policy and standards for all AI/ML risk models in use at PenFed, leading to more optimal use of models, and increased confidence in model outcomes.
- Lead and perform independent model validations, focusing on evaluating model design, data, assumptions, performance and implementation for compliance with organizational and regulatory standards.
- Review and assess model monitoring processes, including identifying and mitigating risks related to model drift, bias, and operational stability.
- Develop and implement AI/ML risk management frameworks, ensuing models meet requirements for interpretability, fairness, robustness, and ethical considerations.
- Provide clear and insightful analysis, feedback, and critique of models by way of written reports and presentations to business units and senior management.
- Collaborate with model owners and stakeholders to ensure alignment on validation findings, monitoring results, and governance expectations.
- Stay current with emerging AI/GenAI risks, technologies, and regulatory guidance to continuously improve validation processes and frameworks.
Other
- Advanced degrees in quantitative subjects, such as Data Science (AI/ML), Economics, Finance, Physics, Mathematics, or related quantitative subjects.
- Minimum of twelve (12) years’ experience in quantitative modeling, risk management, financial research or model risk management in a financial institution.
- Minimum four (4) years of direct management experience required.
- The ability to travel to various worksites and be on-call may be required.
- Ability to condense highly technical subject matter into clear, effective presentation-quality communications to senior management.
