The Model Risk Governance (MRG) group is responsible for designing, implementing, maintaining and enforcing the Model Risk Management program within the Bank. This includes design and execution of policies, standards, and internal procedures for all phases of model life cycle from identification and inventorying to implementation, maintenance,
and retirement. MRG provides oversight of model development and validation and reports on the Bank's overall model risk. This Quantitative Model Analyst supports the MRG function by:
• Identifying, inventorying, and risk rating models.
• Collaborating with business lines, model owners, and model validation to ensure Model Risk Management program requirements are communicated and understood.
• Assessing model documentation, including development, monitoring, and implementation documentation, for completeness against program standards and templates.
• Regularly working with model owners and monitoring existing models to ensure compliance with Model Risk Management program requirements.
• Regularly meeting with the model owners and validators to discuss new models, model changes, redevelopments or retirements, and current model issues.
• Thinking critically about continuous process improvements.
- Bachelor's degree in a quantitative field, and 10 or more years of experience in statistical modeling OR
- Master's or PhD degree in a quantitative field, and six or more years of experience in statistical modeling
• Strong project management skills.
• Advanced knowledge of various regression techniques, parametric and non-parametric algorithms, times series techniques, and other statistical models, various model validation tests/methodologies, using SAS or similar statistical packages.
• Advanced knowledgeable of quantitative and qualitative risk factors, industry risks, competition risks, and risk management approaches.
• Master's or PhD degree in a quantitative field, and at least six years of experience in modeling within the financial services industry.
• Strong statistical modeling experience in Artificial Intelligence and Machine Learning is highly desirable.
• Experience in either model governance or model validation roles.
• Excellent written and verbal communication skills, including the ability to effectively communicate Model Risk Management program requirements to persons or business lines previously unfamiliar with the requirements.
• Advanced understanding of applicable laws, regulations, financial services, and regulatory trends that affect assigned line of business.
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