Job Type
Full-time
Description
The Model Validation Analyst plays a critical role in ensuring model integrity, regulatory compliance, and sound risk management practices. This role reports to the Head of Credit Risk and Portfolio Analytics Credit and supports the Bank's strategic partner program by reviewing statistical models used in underwriting and assessing overall model risk across partnerships.
What You'll Do:- Review third-party model validation documentation for conceptual soundness and alignment with applicable regulatory guidance.
- Assess and challenge credit models and underwriting strategies used in loan origination.
- Maintain a comprehensive inventory of all models used by the Bank, including underwriting, fraud, and marketing models.
- Evaluate model performance monitoring practices and ensure appropriate tracking of key risk indicators.
- Partner with Compliance, Legal, and Strategic Partner Management teams to ensure models meet applicable regulatory and internal policy requirements.
- Prepare reports and present model risk metrics to the Bank's Credit Committee.
- Monitor and test credit origination strategies to validate accuracy and consistency of credit decisions.
- Conduct model and credit risk due diligence for prospective fintech partners.
- Participate in or lead initiatives to enhance model risk management processes and improve overall risk oversight.
Requirements
What We're Looking For:Education & Experience
- Master's degree in Statistics, Data Science, Computer Science, Economics, Mathematics, or a related quantitative field;
- OR Bachelor's degree with 3+ years of relevant experience in model development or validation.
- Prior experience developing and/or validating credit risk models is required.
- 3+ years of experience in banking, financial services, or a related industry is preferred.
Technical Skills
- Strong understanding of statistical modeling techniques, including regression and classification models.
- Ability to evaluate model structure, assumptions, and validation methodologies.
- Familiarity with machine learning models and their application in credit decisioning.
- Proficiency in one or more programming languages/tools, such as SQL, Python, R, or SAS.
- Working knowledge of credit policies and underwriting frameworks.
- Familiarity with CECL models is a strong plus.
Professional Skills
- Ability to work effectively across cross-functional teams, including Compliance, Audit, and Model Risk Management.
- Strong analytical and critical thinking skills with attention to detail.
- Effective written and verbal communication skills, including the ability to present technical concepts to non-technical audiences.
- Strong organizational and prioritization skills in a fast-paced environment.
Additional Information
- Experience working with regulatory, audit, or model risk management frameworks is a plus.
- Proficiency in Microsoft Office Suite (Excel, Word, PowerPoint, Outlook) required.
