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 (Winnipeg)
🏢 Socket.dev
📍 Winnipeg