Enhance AI model validation processes as a Data Scientist with RBC's Enterprise Model Risk team. Engage in research and development while addressing critical model risks in banking.

In this vital role at RBC, you will assess and manage AI-related model risks while validating advanced applications and systems. Your responsibilities include challenging model assumptions and improving model explainability and fairness. Collaborating with cross-functional teams enhances your impact on achieving sound risk management and trusted client service across RBC's offerings.

Key Responsibilities:



• Validate LLM-based applications and risk management systems • Challenge AI models conceptually and empirically • Collate insights from research to refine validation techniques • Develop software packages based on validated models • Work collaboratively on MLOps best practices with IT stakeholders

Requirements: • Master’s or PhD candidate in Statistics, Computer Science, or related field • Solid programming skills in Python and familiarity with LLMs • Interest in developing reusable AI validation tools • Communication skills to convey complex concepts • Risk-oriented mindset to explore how and why models function

Drive innovation and refine risk assessment practices with RBC's dedicated AI validation team. #J-18808-Ljbffr

📌 Data Scientist Role in AI Model Risk (Toronto)
🏢 Socket.dev
📍 Toronto