Director, Counterparty Credit Risk Models, Global Risk Analytics

Toronto, ON
On-site
Posted Oct 8, 2026
1 position

Opens an external site

Employment type: Full-time
Experience level: Lead · 10+ years
Minimum education: Master’s degree
Posting language: English
Working hours: 38 hours per week

Job summary

The Director leads a team responsible for the conceptual design, development, and maintenance of mathematical models for counterparty credit risk measurement. They also ensure model integrity, facilitate regulatory compliance, and provide technical guidance to technology teams for production deployment.

Job details

Job Description What is the Opportunity? As part of the Group Risk Management team, the Director, Counterparty Credit Risk Analytics leads a team which is responsible for the conceptual design, development, and ongoing maintenance of the mathematical models used for the measurement and capitalization of the counterparty credit risk of RBC's derivative and SFT portfolio. This includes ensuring that the model's underlying methodologies are appropriate and that they are implemented with integrity, to facilitate the effective management of the bank's CCR. What will you do? Work with model users to understand their business requirements. Conduct research, review regulatory requirements and consult with industry stakeholders to evaluate best practices for modeling. Make recommendations on model methodologies, and develop technical implementation, either for production usage or to serve as a prototype for benchmark testing. Provide business requirements with technical implementation details and user acceptance criteria to technology teams for production deployment, and validate implementation using independently developed benchmark models. Document model methodologies, implementation details and testing results, and work with internal validation to facilitate their approval of the models. Develop tools to assess and monitor model performance, including assumptions and limitations, on an ongoing basis for reporting to the various model monitoring governance committees. Investigate and remediate modeling issues identified through regular re-reviews, ongoing monitoring or by internal validation. Recalibrate models on a regular basis. Re-assessment and testing of models, including assumptions and limitations and benchmarking against alternative models, and documentation of the results in models whitepapers and annual assessments for review by internal validation. What do you need to succeed? Must Have: Broad knowledge of traded products across various asset classes. Understanding of regulatory requirements and industry best practices for the measurement and management of counterparty credit risk. Strong analytical and problem solving skills. Excellent programming skills (e.g., Python). Strong data management and analysis skills (e.g. SQL and Excel). Ability to work collaboratively to achieve team goals. Agility to adapt to changing circumstances in a dynamic environment. Experience managing a team. Strong English communication skills, both written and verbal, especially in the explanation of complex modeling concepts to senior management and regulators. Nice-to-Have: Masters in Financial Engineering, or a degree in another quantitative subject such as physics, statistics, mathematics or mathematical finance and/or a relevant professional qualification, with concentration in quantitative methods and/or finance. What is in it for you? We thrive on the challenge to be our best, progressive thinking, to keep growing, and working together to build and deliver trusted reporting to help our stakeholders succeed and communities prosper. We care about each other, reaching our potential, making a difference to our communities, and achieving success that is mutual. 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 Job Skills Analytical Thinking, Complex Modeling, Counterparty Credit Risk (CCR), Counterparty Risk, Counterparty Risk Management, Financial Engineering, Mathematical Finance, Mathematics Modeling, Model Development, Model Risk, Risk Analytics, Risk Management, Risk Models Additional Job Details Address: ROYAL BANK PLAZA, 200 BAY ST:TORONTO City: Toronto Country: Canada Work hours/week: 37.5 Employment Type: Full time Platform: GROUP RISK MANAGEMENT Job Type: Regular Pay Type: Salaried Posted Date: 2026-08-13 Application Deadline: 2026-10-23 Note: Applications will be accepted until 11:59 PM on the day prior to the application deadline date above Our Employment Opportunities At RBC, we are guided by living shared values of Client First, Integrity, Collaboration, Respect and Excellence and winning together as One 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. Join our Talent Community Stay in-the-know about great career opportunities at RBC. Sign up and get customized info on our latest jobs, career tips and Recruitment events that matter to you. Expand your limits and create a new future together at RBC. Find out how we use our passion and drive to enhance the well-being of our clients and communities at jobs.rbc.com. RBC is presently inviting candidates to apply for this existing vacancy. Applying to this posting allows you to express your interest in this current career opportunity at RBC. Qualified applicants may be contacted to review their resume in more detail.

What you’ll do

Requirements

Candidates must possess broad knowledge of traded products, strong programming skills in Python, and experience in managing a team. A master's degree in financial engineering or a related quantitative field is preferred.