Please Note - Location can be in either Toronto or Halifax

What is the opportunity?

RBC is a global leader in applying Artificial Intelligence (AI) in the banking sector in order to create value for our clients. A failure to effectively prepare for and manage emerging model risk related to AI would subject RBC to financial, regulatory, and reputational risks. Therefore, the AI validation team within RBC’s Enterprise Model Risk Management (RBC Group Risk Management) is tasked with overseeing, assessing, and managing model risks.

The AI validation team uses machine learning, statistical, and computational strategies to assess model risk. In doing so, RBC is able to identify model weaknesses early and enhance the reliability of production models across all lines of business.

What will you do?

• Application: Work with a large variety of model types and with business functions across the bank, such as the following:
  • Types of Models: Classification, Large Language Models (LLM), regression, anomaly detection, natural language processing, computer vision, reinforcement learning, recommendation systems, dimensionality reduction
  • Business Functions: Internal Audit, Cybersecurity, Fraud Management, Anti-Money Laundering, Insurance, Credit Risk, Technology Operations, Identity & Access Management, Human Resources
• Validation: Challenge models and identify risks associated with their use – both conceptually and empirically.
• Research & Development: Read research papers to enhance how our team validates models and contribute to our knowledge pool. You are encouraged to apply what you’ve learned to real-world problems, develop reusable software packages, and share your insights with others.
• IT: Collaborate with cross-functional stakeholders to establish and promote best-practices related to MLOps, tooling and IT infrastructure.
• Governance: Work with model developers (data scientists, researchers, engineers) and business stakeholders to inventory applications of AI and machine learning

What do you need to succeed?

Must-have

• Master’s or PhD degree in Statistics, Computer Science, Applied Mathematics, Econometrics, Engineering, Quantitative Finance, or a related quantitative field
• Proficient programming skills in Python or a similar language; you should already be comfortable with writing research experiments and be willing to learn how to write clean code.
• Familiarity with popular machine learning frameworks and libraries
• Passionate about learning and staying up-to-date with research and technology
• A risk-oriented mindset: You are curious about the “how” as well as the “why"
• Strong communication and interpersonal skills

Nice-to-have

• Publication or prior research experience (applied or fundamental)
• Experience with version control systems
• Comfortable with command line tools

What’s in it for you?

We thrive on the challenge to be our best, progressive thinking to keep growing, and working together to deliver trusted advice to help our clients thrive 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 and competitive compensation
• Leaders who support your development through coaching and managing opportunities
• Work in a dynamic, collaborative, progressive, and high-performing team
• Opportunities to do challenging work