Manager- R&C

Introduction

The Model Validation Analyst independently evaluates the conceptual integrity, performance, implementation, and ongoing monitoring of models deployed throughout the Bank. This role reinforces the Bank’s Model Risk Management (MRM) framework by executing thorough validations aligned with regulatory requirements, including the U.S. Federal Reserve’s SR 26-2 Guidance on Model Risk Management and relevant OCC and FDIC expectations.

The analyst will review a range of quantitative and qualitative models, such as credit risk, market risk, liquidity risk, stress testing, AML/fraud, capital planning, CECL, pricing, and machine learning models. Reporting under the supervision of the U.S. team, the successful candidate will partner closely with the Bank’s MRM team, model developers, model owners, business stakeholders, Internal Audit, and regulators to confirm that models are fit for purpose and that associated risks are identified and mitigated appropriately.

Your Role And Responsibilities

• Conduct independent model/EUC validations and reviews across the model lifecycle, under supervision of the U.S. team.
• Evaluate model conceptual design, methodology, assumptions, limitations, data quality, implementation, and usage.
• Perform quantitative testing, including:
• Outcome analysis
• Benchmarking
• Back-testing
• Sensitivity analysis
• Stress testing
• Performance monitoring reviews
• Review model development documentation and related supporting evidence.
• Confirm adherence to internal model risk policies and regulatory guidance.
• Document validation findings and assign risk ratings according to established governance standards.
• Create recommendations to improve models and mitigate risk.
• Support maintenance of the model inventory, model risk ratings, and issue tracking and remediation activities.
• Coordinate with the bank MRM team, model developers, business units, risk management teams, and technology teams.
  

Preferred Education

Master's Degree

Required Technical And Professional Expertise

Education

• Bachelor's degree in Statistics, Mathematics, Economics, Finance, Data Science, or related quantitative discipline
  
  

Experience

• 2-5 years of experience in model validation, model development, quantitative analytics, data science, risk management, or related fields within banking or financial services, preferably for U.S. clients.
• Knowledge of model risk management frameworks and regulatory expectations.
• Experience validating or developing risk, financial, or machine learning models is preferred.
  
  

Technical Skills

• Strong command of statistical and quantitative modeling techniques.
• Knowledge of:
• Regression analysis
• Time series forecasting
• Classification models
• Machine learning methodologies
• Probability and statistical inference
• Proficiency in one or more programming languages:
• Python
• R
• SAS
• SQL
• Experience working with large datasets and analytical tools.
  

Preferred Technical And Professional Experience

Master's degree in a quantitative field.

Experience validating:

• Credit risk models
• CECL models
• Stress testing models
• Market risk models
• AML/Fraud models
• Machine learning and AI models
• Experience or familiarity with:
• SR 26-2 Model Risk Management Guidance
• OCC Model Risk Management expectations
• CECL framework
• Basel regulations
• Fair Lending and model governance requirements
• AI/ML model risk considerations
  
  

Competencies

• Strong analytical and critical thinking abilities.
• Capacity to independently challenge complex quantitative methods.
• Excellent written and verbal communication skills.
• Strong report-writing and documentation capabilities.
• High attention to detail and commitment to quality.
• Ability to handle multiple projects and competing deadlines.
• Strong stakeholder engagement and relationship management skills.
  
  

Key Deliverables

• Thorough model validation reports.
• Validation test workpapers and related supporting documentation.
• Findings and remediation tracking.
• Model performance monitoring assessments.