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Data Scientist, AI Model Risk
RBC
Vancouver, CAN
Full-time
Onsite
Discovered 1 weeks ago
Artificial intelligenceAI model validationMachine learningLLM validationAgentic AI systemsPython
Free
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Artificial intelligenceAI model validationMachine learning
Role Overview
RBC's AI validation team within Enterprise Model Risk Management assesses and manages model risk arising from AI capabilities.
The team uses machine learning, statistical, and computational strategies to identify model weaknesses and improve production model reliability.
Key Skills for This Role
Artificial intelligenceAI model validationMachine learningLLM validationAgentic AI systemsPython
Full Job Posting
Opportunity Overview
RBC's AI validation team within Enterprise Model Risk Management assesses and manages model risk arising from AI capabilities.
The team uses machine learning, statistical, and computational strategies to identify model weaknesses and improve production model reliability.
Core Responsibilities
- Validate LLM-based applications and agentic AI systems, with possible work on traditional machine learning models.
- Challenge models and identify conceptual and empirical risks associated with their use.
- Assess conceptual soundness, metric reproducibility and stability, benchmarking, uncertainty, fairness, privacy, explainability, and implementation controls.
- Develop models, reusable software packages, and tools while contributing research insights to the team.
- Collaborate with cross-functional stakeholders on MLOps, tooling, and IT infrastructure best practices.
Business Collaboration
- Work with teams across internal audit, cybersecurity, fraud management, anti-money laundering, insurance, credit risk, technology operations, identity and access management, and human resources.
- Read established and state-of-the-art research papers and apply findings to real-world validation problems.
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