As a Senior Model Risk Management Analyst, you will play a central role in evaluating and overseeing the integrity of models used across the organization and its fintech partnerships. Your work ensures adherence to regulatory standards and sound risk practices from development through ongoing monitoring.
Key Responsibilities
- Monitor model performance and usage across partner institutions throughout the model lifecycle
- Track and analyze key risk indicators to assess model effectiveness and reliability
- Review technical documentation for models including scorecards, regression techniques, and machine learning algorithms
- Support the upkeep of the enterprise model inventory and classification framework
- Contribute to due diligence during onboarding of new fintech partners, focusing on model risk controls
- Collaborate with program managers, risk, finance, compliance, and legal teams to proactively manage model-related risks
- Develop and deliver risk metrics and reports for executive committees and governance forums
- Respond to evolving priorities in a fast-paced environment with shifting demands and timelines
Qualifications
Candidates must hold a bachelor’s or advanced degree in a quantitative field such as mathematics, statistics, econometrics, physics, or financial engineering. A minimum of five years of experience in model validation, statistical modeling, or model risk management is required.
Proficiency in both traditional statistical methods—like linear and logistic regression—and modern machine learning approaches—including gradient boosting—is essential. You should have a solid understanding of financial products, regulatory expectations, and industry standards related to model risk.
Strong communication skills are critical, as you will need to translate complex technical findings into clear insights for diverse audiences. Success in this role requires adaptability, collaboration, and the ability to thrive in a dynamic, regulated environment.
