Drive innovation in AI risk management at RBC as a Data Scientist focused on validating LLM applications. Collaborate cross-functionally while mitigating emerging model risks across banking applications. As a Data Scientist in RBC’s AI validation team, you are integral to ensuring robust risk assessment of AI models.

This role combines validation of LLM-based applications and traditional machine learning models, including anomaly detection and NLP. Your insights will enhance model stability, fairness, and explainability, ultimately supporting RBC's commitment to high-quality client service. Key Responsibilities:

- Collaborate with business functions like Cybersecurity and Fraud Management
- Validate LLM-based applications and traditional machine learning systems




- Assess risks associated with AI model implementation accurately
- Read research papers and apply findings to real-world challenges
- Promote best practices in MLOps and IT infrastructure Requirements:
- Progress towards a PhD or Master’s degree in a quantitative field
- Proficient in Python with hands-on coding experience
- Familiarity with popular LLMs and agentic frameworks
- Robust communication and interpersonal skills
- Passionate about research and technology trends Contribute to cutting-edge AI model validation at RBC and strengthen risk management across banking.

📌 AI Model Risk Scientist at RBC (Toronto)
🏢 Socket.dev
📍 Toronto