2026 Fall - GRM, Data Science Intern (4 Months)

Job Description RBC is a global leader in applying Artificial Intelligence (AI) in the banking sector to create value for our clients, with capabilities ranging from LLM-powered digital banking, boosting ensembles in fraud detection and AML, voice assistants in customer service, to algorithmic trading in capital markets. A failure to effectively prepare for and manage emerging model risk related to AI would subject RBC to financial, regulatory, and reputational risks and, as a result, RBC would not be able to provide its clients with the best quality service. Therefore, the AI validation team within RBC's Enterprise Model Risk Management is tasked with overseeing, assessing, and managing the model risk that may arise from these AI capabilities.

What will you do? Application: You will have the opportunity to work in any of the many areas we work in, across an even wider variety of business functions.

Types of Models Classification, regression, anomaly detection, natural language processing, computer vision, reinforcement learning, recommendation systems, dimensionality reduction, Large Language Models including generative AI.

Business Functions Internal Audit, Cybersecurity, Fraud Management, Anti-Money Laundering, Insurance, Credit Risk, Technology Operations, Identity & Access Management, Human Resources.

Responsibilities

Validation: Challenge models and identify risks associated with their use – both conceptually and empirically. Design and execute validation frameworks, exploring modelling considerations such as conceptual soundness, data processing, metric reproducibility & stability, benchmarking, robustness, uncertainty quantification, fairness, privacy, explainability, implementation controls and more. Explore ideas that interest you and build your own models and tools.

Research & Development: Read research papers (established work and state-of-the-art) to enhance how the team validates models and contribute to the knowledge pool. Apply what you learn to real-world problems, develop reusable software packages, and share 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 at the bank, determine their materiality, and assess whether they require review.

What do you need to succeed? Must-have Skills

Passionate about learning and staying up-to-date with research and technology.

Strong communication and interpersonal skills.

Progress towards a PhD, Master’s, or Bachelor’s 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; comfortable writing research experiments and learning to write clean code.

Familiarity with popular machine learning frameworks and libraries.

Nice-to-have Skills

A risk-oriented mindset: curiosity about the "how" as well as the "why".

Publication or prior research experience (applied or fundamental).

Experience with version control systems.

Comfortable with command line tools.

Benefits As a team, we thrive on the challenge to be our best, encourage progressive thinking for continued growth, and collaborate with one another to deliver trusted advice to help our clients thrive and our communities prosper. We respect and care about all of our team members and support one another in reaching our fullest potential. We work together to make a difference in our communities and to achieve success that is mutual.

Leaders who support your development through coaching and managing opportunities.

Flexibility to work on projects that you are passionate about.

Ability to make a difference and lasting impact.

Work in a dynamic, collaborative, progressive, and high-performing team.

Eligibility and Terms This posting is for a 4-months Fall 2026 Student placement with a start date of September 2026 and an end date of December 2026. Eligible candidates must either, be returning back to school after the work term end-date of December 2026, or if not returning to school (i.e. graduating in December 2026), require the full 4-months work term as a mandatory component to graduate successfully.

Please ensure that you meet these eligibility requirements before applying; candidates who apply but are found to be ineligible are not considered.

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