remote
Data Scientist, AI Model Risk - RBC
Data Scientist
Data Scientist specializing in AI model risk, responsible for validating, monitoring, and mitigating risks of AI/ML models in banking, using Python, statistical techniques, and regulatory frameworks to ensure safe, compliant AI deployment.
About the role
Key Responsibilities
- Design and execute validation frameworks for AI/ML models used across banking products, ensuring they meet regulatory and internal risk standards.
- Develop statistical tests, performance metrics, and monitoring dashboards to detect model drift, bias, and unintended outcomes.
- Collaborate with model owners, data engineers, and compliance teams to document model lineage, assumptions, and mitigation strategies.
- Produce clear risk assessment reports and recommendations for model remediation or retirement.
- Stay current with emerging AI regulations and industry best practices, integrating them into the enterprise model risk management process.
Requirements
- Advanced degree (MSc/PhD) in Computer Science, Statistics, Applied Mathematics, or related field.
- 5+ years of hands‑on experience with Python, statistical modeling, and machine‑learning libraries (e.g., scikit‑learn, TensorFlow, PyTorch).
- Demonstrated expertise in AI/ML model risk assessment, including bias detection, explainability, and regulatory compliance.
- Strong analytical and communication skills, with the ability to translate technical findings into actionable business recommendations.
- Experience working in highly regulated financial services environments is preferred.
Skills
pythonmachine learning