Introduction

The Model Validation Analyst is responsible for independently assessing the conceptual soundness, performance, implementation, and ongoing monitoring of models used across the Bank. The role supports the Bank's Model Risk Management (MRM) framework by conducting rigorous validations in accordance with regulatory requirements, including the U.S. Federal Reserve's SR 26-2 Guidance on Model Risk Management and applicable OCC and FDIC expectations.

The analyst will evaluate a variety of quantitative and qualitative models, including credit risk, market risk, liquidity risk, stress testing, AML/fraud, capital planning, CECL, pricing, and machine learning models. The successful candidate will work under the supervision of the U.S. team, work closely with bank MRM team, model developers, model owners, business stakeholders, Internal Audit, and regulators to ensure models are fit for purpose and risks are appropriately identified and mitigated.

Your Role And Responsibilities

Perform independent validations and reviews of models/EUCs across the model lifecycle under supervision of the US team.
Assess model conceptual design, methodology, assumptions, limitations, data quality, implementation, and usage.
Conduct quantitative testing, including:

Outcome analysis
Benchmarking
Back-testing
Sensitivity analysis
Stress testing
Performance monitoring reviews

Evaluate model development documentation and supporting evidence.
Verify compliance with internal model risk policies and regulatory guidance.
Assign validation findings and risk ratings based on established governance standards.
Develop recommendations for model improvements and risk mitigation.
Assist in maintaining the model inventory, model risk ratings, and issue tracking and remediation.
Collaborate with 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.
Familiarity with model risk management frameworks and regulatory expectations.
Experience validating or developing risk, financial, or machine learning models is preferred.

Technical Skills

Strong understanding 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 skills.
Ability to independently challenge complex quantitative methodologies.
Excellent written and verbal communication skills.
Strong report-writing and documentation capabilities.
Attention to detail and commitment to quality.
Ability to manage multiple projects and deadlines.
Strong stakeholder engagement and relationship management skills.

Key Deliverables

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

Deputy Group Manager-R&C