Senior Data Scientist - AI Governance

Job Summary

• Responsible for designing and enforcing the framework that ensures our AI and Machine Learning models are ethical, compliant, and technically robust.
• Responsible for overseeing and validating the entire AI/ML lifecycle from experimentation, model design and development to MLOps (model operationalization) across the enterprise, ensuring
• Responsible AI best practices.
• Responsible for conducting due diligence on 3 rd party AI/ML providers and Gen AI applications.
  
  

• ML Development Governance: Establish standards for data lineage, feature engineering, and algorithm selection to ensure models are built on high-quality, unbiased foundations. Ensure proper audit-ready documentation of model design, development process and model approval.
• ML Operationalization (MLOps) Oversight: Define governance gates for CI/CD pipelines, ensuring automated testing, version control, and audit trails are mandatory for all production deployments. Ensure proper audit-ready documentation of model operationalization processes.
• Bank-Wide Model Stewardship: Align AI/ML initiatives with global banking regulations. You will ensure that models used in credit, fraud, and marketing meet institutional risk appetites.
• Develop and maintain the bank-wide AI/ML asset inventory.
• AI Ethics & Policy: Coordinate with policy makers and enforce regulations / policies regarding AI, Generative AI, LLM usage, and data privacy, staying ahead of evolving AI specific legislation. Develop / enhance AI Risk Classification and mandates / monitors required risk governance assessment per tier.
• Model Validation & Stress Testing: Lead rigorous independent validation processes, including sensitivity analysis, back-testing, and "challenger model" assessments to identify potential failures before they impact the business.
• Due Diligence of Outsourced AI/ML Models or Solutions: Conduct due diligence on the models developed by vendors, including testing of 3rd party providers of AI/ML solutions within RCBC and subsidiaries.
• Support business initiatives by responding to ad hoc requests from business advocates most especially high-priority projects.
  
  

• Degree in Mathematics, Statistics, Computer Science, Management Information Systems, or related field
• Minimum 5+ years of total technical experience, with at least 2 years dedicated to Model Risk Management (MRM), AI Audit, or Governance.
• Experience in enforcing Reponsible or Ethical AI frameworks; Experience interacting with or preparing documentation for audit or regulators
• The ability to "speak tech" with Data Scientists and "speak risk" with Internal Audit and Regulators; Demonstrates professional integrity; with a high sense of urgency, highly analytical.