The Model Risk & Validation Specialist is responsible for independently reviewing and monitoring models to ensure they remain reliable, fit for purpose, and compliant with model risk management standards and BSP regulatory requirements.
The role covers model validation, model monitoring, effective challenge, issue tracking, and model risk oversight across various banking and risk models.
Key Responsibilities
Model Validation & Review
- Conduct independent reviews of risk and Non-AI/ML models prior to implementation.
- Assess model methodology, assumptions, data sources, performance, limitations, documentation, and intended use.
- Review model changes, including recalibration, redevelopment, methodology changes, and changes in model application or scope.
- Identify model risks and gaps and provide effective challenge and recommendations.
Model Monitoring
- Review model monitoring results and assess performance metrics, thresholds, stability indicators, back-testing results, and model limitations.
- Identify performance deterioration, threshold breaches, emerging risks, and concerns regarding continued model fitness.
- Evaluate root-cause analyses and proposed remediation plans.
- Recommend appropriate actions, including recalibration, enhancement, redevelopment, watchlisting, or retirement.
Reporting & Model Risk Management
- Prepare model validation reports, monitoring assessments, and other model risk documentation.
- Track findings, remediation plans, and closure of identified issues.
- Support model inventory, validation tracking, monitoring dashboards, and regulatory reporting.
- Support Model Risk Management Framework initiatives and BSP regulatory requirements.
Qualifications
- Bachelor's degree in Statistics, Mathematics, Economics, Data Science, Engineering, Finance, Risk Management, Computer Science, or a related quantitative field.
- At least 5 years of experience in Model Validation, Model Risk Management, Model Monitoring, Risk Analytics, Quantitative Analytics, or a related function.
- Strong analytical, critical-thinking, and technical documentation skills.
- Experience in banking, financial services, IFRS 9/ECL, credit risk models, or other banking risk models is preferred.
- Experience with SQL, Python, R, SAS, or similar analytical tools is an advantage.
Key Skills
Model Validation • Model Risk Management • Model Monitoring • Risk Analytics • Quantitative Analysis • IFRS 9/ECL • Credit Risk • Model Governance • Statistical Analysis
