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