Senior Model Risk & Validation Lead (Credit Risk)

RBC; Toronto; On-site; CAD 120,000 - 160,000; Full time

Benefits offered by this job

Total rewards

Bonuses

Flexible benefits

Career development

Job summary

RBC in Toronto is seeking an Associate Director, Enterprise Model Risk Management to lead end-to-end validation of credit risk models for the Canadian Banking platform. You will assess model soundness, review data inputs and documentation, and communicate findings with clear recommendations.

The role requires 3+ years in model development or validation, hands-on AI/ML (deep learning, XGBoost) and logistic regression, Python programming and SQL, and a postgraduate degree in a quantitative field.

Qualifications

• 3+ years of model development or validation experience in credit risk.
• Hands-on AI/ML techniques (deep learning, XGBoost) and logistic regression.
• Proficient Python programmer with a track record of delivering high-quality code.
• Experience with large datasets; SQL data extraction and data mining.
• Postgraduate degree in a quantitative field (e.g., stats, CS, applied mathematics).

Responsibilities

• Conduct end-to-end validation of credit risk models and document results.
• Review data inputs/outputs and ensure compliance with policy.
• Develop comprehensive reports with observations, conclusions and recommendations.
• Collaborate with model developers and stakeholders.
• Plan validations per policy timelines based on materiality and uncertainty.

Skills

Python programming

SQL

AI/ML techniques

Data mining

Communication skills

Education

Postgraduate degree in quantitative field

Tools

Hadoop

Spark

Tableau

Git

Object storage

Job description

RBC in Toronto is seeking an Associate Director, Enterprise Model Risk Management to lead end-to-end validation of credit risk models for the Canadian Banking platform. You will assess model soundness, review data inputs and documentation, and communicate findings with clear recommendations.

The role requires 3+ years in model development or validation, hands-on AI/ML (deep learning, XGBoost) and logistic regression, Python programming and SQL, and a postgraduate degree in a quantitative field.