Associate Director, Credit Risk Modeling and Methodology

RBC; Toronto; On-site; CAD 90,000 - 120,000; Full time

Job summary

A leading financial institution in Toronto is seeking an Associate Director for Credit Risk Modeling and Methodology. The role involves supporting model development and monitoring, ensuring data accuracy, and compliance with regulatory standards. Candidates should have a degree in a quantitative field, along with 3-5 years of experience in risk management or data analytics. Strong skills in Python, SAS, and SQL are essential. The position offers a comprehensive rewards program and the opportunity to work in a dynamic, collaborative team.

Benefits

Comprehensive Total Rewards Program

Dynamic, collaborative work environment

Opportunities for progression

Qualifications

• 3–5 years of related experience in risk management, data science, or data analytics.
• Strong data manipulation capability and analytical skills with advanced knowledge in Python, SAS, SQL.
• Effective communication to translate technical expertise into business language.

Responsibilities

• Perform quarterly monitoring of AIRB, IFRS 9, and Stress Testing models.
• Provide data preparation support for credit risk models.
• Lead initiatives to enhance data quality across systems.
• Ensure compliance with regulatory requirements.
• Identify and implement process improvements for data analytics.
• Develop and maintain comprehensive documentation of data processes.

Skills

Data manipulation capability

Analytical skills

Communication skills

Knowledge in Python

Knowledge in SAS

Knowledge in SQL

Education

Degree in a quantitative field (Statistics, Computer Science, Finance, Economics, Business Administration)

Tools

MS Office Suite

Tableau

Job description

Overview

The Associate Director, Credit Risk Modeling and Methodology will support model development and model monitoring of the credit risk models for RBC’s Retail portfolios from a data analytics and portfolio management perspective. The role focuses on preparing data for modeling retail parameters: PD/LGD/EAD and back‑testing parameter performance, ensuring data accuracy, consistency, and regulatory compliance, and assisting the Director in executing and maintaining tools and processes that support model development and performance monitoring.

Responsibilities

• Model Performance Monitoring and Reporting: Perform the quarterly monitoring process for AIRB, IFRS 9, and Stress Testing models, ensuring quarterly regulatory reports reflect the bank’s true loss experience and provisioning. Analyze trends, variances, and potential data/model issues that may arise during the monitoring process.
• Analytics for Credit Risk Models: Provide expert support on data preparation and manipulation for AIRB and IFRS 9 credit risk models and Stress Testing models, for example, constructing cohorts, conducting pattern analysis, and inferring the potential impacts on parameters and modeling. Collaborate closely with stakeholders including modeling team, credit strategy team, validation team and provide advanced level analytical support.
• Data Quality Management: Lead initiatives to monitor, assess, and enhance data quality across various systems. Understand retail products (mortgages, lines of credits, credit cards, etc.) and apply the knowledge to detect data anomalies, product evolvements, gaps, or issues that could impact model performance or regulatory reporting.
• Regulatory Compliance and Stakeholder Engagement: Ensure all processes and reports comply with relevant regulatory requirements and internal modeling standards. Work with model validation, internal audit and regulators as necessary, providing analytical insights and recommendations.
• Continuous Improvement: Identify opportunities for process improvements and implement best practices to enhance the efficiency and effectiveness of data analytics in credit risk modeling.
• Documentation and Standards: Develop and maintain comprehensive documentation of data processes, standards, and quality controls, ensuring documents are up-to-date and accessible to relevant stakeholders.

Qualifications

• Degree in a quantitative field of study (e.g., Statistics, Computer Science, Finance, Economics, Business Administration).
• 3–5 years of related experience with in-depth knowledge in risk management, data science, or data analytics.
• Strong data manipulation capability and analytical skills with advanced knowledge in Python, SAS, SQL and expertise with MS Office Suite.
• Effective communication, translating technical expertise into business language that drives insights.

Nice-to-have

• Experience in the financial industry.
• Demonstrated leadership in cross‑functional environments.
• Strong credit risk modeling knowledge and understanding of consumer lending products such as mortgages, credit cards, lines of credits, etc.
• Advanced knowledge and working experience with data management and data visualization using tools including Tableau.

Benefits

• A comprehensive Total Rewards Program including bonuses and flexible benefits, competitive compensation.
• Ability to make a difference and lasting impact.
• Work in a dynamic, collaborative, progressive, and high‑performing team.
• Opportunities to take on progressively greater accountabilities.

EEO Statement

At RBC, we believe an inclusive workplace that has diverse perspectives is core to our continued growth as one of the largest and most successful banks in the world. Maintaining a workplace where our employees feel supported to perform at their best, effectively collaborate, drive innovation, and grow professionally helps to bring our purpose to life and create value for our clients and communities. RBC strives to deliver this through policies and programs intended to foster a workplace based on respect, belonging and opportunity for all.