Data Scientist, AI Model Risk
Core
Validating AI and machine learning models within a global bank to assess model risk, ensure reliability, and manage regulatory compliance for AI capabilities.
Role type
AI Model Risk Validation Engineer
Builds
Validated AI models and agentic systems for banking operations
Domain
Banking / Artificial Intelligence / Model Risk Management
Deliverable
production ML models
Required skills
Python programming, LLM and agentic frameworks, statistical analysis, uncertainty quantification, fairness assessment, explainability analysis, MLOps collaboration
Preferred skills
PhD or Master's in quantitative field, research experience, version control, command line tools, traditional ML frameworks
Technologies
Python, LLMs, agentic frameworks, MLOps tools
Responsibilities
Validate LLM-based applications and agentic AI systems, challenge models to identify conceptual and empirical risks, explore modeling considerations like benchmarking and privacy, read research papers to enhance validation methods, collaborate on MLOps best practices
Seniority
Mid-Senior, hands-on IC