Manager, Enterprise Risk Model Management

What is your opportunity? You will work in close proximity with model stakeholders in order to vet and validate mathematical/statistical models used by RBC, mainly focusing on Credit Risk (PD/LGD/EAD/etc.) for IFRS 9 and EWST. You will also act as a trusted advisor and effective challenger to model developers and users on all matters pertaining to risk‑modeling requirements.

• Perform effective challenge of model inputs, methodology, and implementation.
• Independently build replication/benchmarking models using statistical and/or machine‑learning algorithms.
• Engage model developers and related function‑group personnel as necessary to proactively assess, document, and independently validate mathematical/statistical models and their usage by the bank.
• Acquire and maintain a thorough understanding of the flow and context of model usage by the business.
• Ensure that model users adhere to RBC model risk policy.

• Graduate degree in a quantitative discipline such as physics, mathematics, engineering, computer science, statistics, finance or financial engineering. Strong academic and research background may also count towards work experience.
• Minimum one year experience in mathematical/statistical modeling in a similar or related role such as a model developer/validator, a front‑office quant, a risk quant, or a risk manager.
• Proficient in model development in SAS, Python or another programming language.

• Broad exposure to and excellent knowledge of a wide range of financial models and model‑validation/testing techniques.
• Exceptional analytical, statistical, computational, and critical‑thinking skills.

• A comprehensive Total Rewards Program including bonuses and flexible benefits.
• Leaders who support your development through coaching and management opportunities.
• Ability to make a difference and lasting impact.
• Work in an agile, collaborative, progressive, and high‑performing team.
• The opportunity to interface with executives from many different parts of the organization.

• Actuarial modeling
• Business analytics
• Credit analysis
• Financial regulation
• Internal auditing
• Investment risk management
• Predictive analytics
• Risk management
• Standard operating procedure (SOP)
• Statistical analysis