Data Scientist, AI Model Risk

RBC; Toronto; On-site; CAD 110,000 - 170,000; Full time

Job summary

RBC, a global financial leader, seeks an AI validation professional in Toronto to assess and manage model risk arising from AI initiatives. The role focuses on validating LLM-based apps and agentic AI systems within Enterprise Model Risk Management.

You will explore conventional ML methods, collaborate across functions, and contribute to reusable software packages while applying state-of-the-art research to real-world problems.

Qualifications

• Pursuit of a PhD or Master’s degree in a quantitative field such as statistics, CS, applied mathematics, econometrics, engineering, or quantitative finance.
• Proficient Python; able to write and run research experiments and clean code.
• Familiar with popular LLMs and agentic frameworks.
• Strong communication and interpersonal skills.

Responsibilities

• Validate LLM-based applications and agentic AI systems, and assess associated risks.
• Validate traditional ML models (classification, regression, NLP, RL, recommender systems).
• Challenge models conceptually and empirically, focusing on soundness, reproducibility, fairness, privacy, and explainability.

Skills

Python

Statistics

LLMs

Research

Communication

Education

Masters/PhD in related quantitative field

Tools

Git

Linux

ML Frameworks

Job description

Job Description

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, with capabilities ranging from LLM-powered digital banking to voice assistants in customer service. 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 our clients with the best quality service. Therefore, the AI validation team within RBC's Enterprise Model Risk Management (RBC Group Risk Management) is tasked with assessing, and managing the model risk that may arise from these AI capabilities.

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, with capabilities ranging from LLM-powered digital banking to voice assistants in customer service. 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 our clients with the best quality service. Therefore, the AI validation team within RBC's Enterprise Model Risk Management (RBC Group Risk Management) is tasked with assessing, and managing the model risk that may arise from these AI capabilities.

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: You will have the opportunity to collaborate with teams across a wide variety of business functions, such as the following: Internal Audit, Cybersecurity, Fraud Management, Anti-Money Laundering, Insurance, Credit Risk, Technology Operations, Identity & Access Management, Human Resources.
• Technical Scope: Your primary focus will be on validation of LLM-based applications and agentic AI systems. This role may also involve validating traditional machine learning models, including classification, regression, anomaly detection, natural language processing, reinforcement learning, and recommendation systems.
• Validation: Your role is to challenge models and identify risks associated with their use – both conceptually and empirically. To that end, you will explore modelling considerations such as conceptual soundness, metric reproducibility & stability, benchmarking, uncertainty quantification, fairness, privacy, explainability, implementation controls and more. You will also have the freedom to explore ideas that interest you and build your own models and tools.
• Research & Development: You will read research papers (established work and state-of-the‑art) 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: You will collaborate with cross-functional stakeholders to establish and promote best‑practices related to MLOps, tooling and IT infrastructure.

What do you need to succeed?

Must-have

• Passionate about learning and staying up-to-date with research and technology
• Strong communication and interpersonal skills
• Progress towards a PhD or Master's degree in Statistics, Computer Science, Applied Mathematics, Econometrics, Engineering, Quantitative Finance, or a related quantitative field
• Proficient programming skills in Python; you should already be comfortable with writing research experiments and be willing to learn how to write clean code.
• Familiarity with popular LLMs and agentic frameworks.

Nice‑to‑have

• A risk‑oriented mindset: You are curious 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
• Familiarity with popular machine learning frameworks and libraries

What's in it for you?

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.

This opportunity will provide you with:

• Work in a dynamic, collaborative, progressive, and high-performing team
• Opportunities to do challenging work, make a difference and lasting impact
• Continuous learning and flexibility to work on projects that you are passionate about
• Leaders who support your development through coaching and managing opportunities

#TECHPJ

Job Skills

Artificial Intelligence (AI), Client Counseling, Communication, Critical Thinking, Financial Instruments, Group Problem Solving, Investment Risk Management, Market Risk, Python (Programming Language), Quantitative Methods, Risk Management

Additional Job Details

Address: 180 WELLINGTON ST W: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: 2026-06-24

Application Deadline: 2026-08-31

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.

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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.