This role is responsible for the independent validation and ongoing assessment of Anti-Financial Crime (AFC) analytical models to ensure they meet regulatory expectations, internal standards, and sound model risk management principles. The role contributes to strengthening the bank's AFC analytics capability through robust validation, governance, and continuous improvement of model frameworks.
Key Responsibilities
Model Validation and Review
- Independently validate AFC models in line with the bank's model validation standards and governance requirements.
- Assess the robustness of model design, development methodologies, assumptions, and data integrity.
- Perform detailed reviews of development code to ensure alignment with documented methodologies and outputs.
- Review remediation actions taken by model owners to address issues identified in prior validation exercises.
Reporting and Management Oversight
- Produce comprehensive validation reports documenting findings, risk assessments, and actionable recommendations.
- Translate technical validation outcomes into clear and meaningful insights for senior management.
- Support preparation of regular model performance reports for senior stakeholders across regions.
Framework and Standards Enhancement
- Contribute to the enhancement of AFC model validation standards, methodologies, and frameworks.
- Stay updated on evolving regulatory requirements, industry best practices, and analytical advancements related to AFC risk management.
- Propose enhancements to model development and validation standards in consultation with team leadership.
Planning and Infrastructure Support
- Assist in planning and coordinating the model validation calendar across portfolios.
- Support initiatives related to analytical systems, infrastructure, and databases used in model development and validation activities.
Job Requirements
Education and Experience
- Undergraduate degree in a quantitative discipline such as data science, statistics, mathematics, or engineering.
- 58 years of experience in analytics or technology roles, with 23 years in advanced data analytics preferred.
- Prior experience working on large-scale analytics or data-driven projects.
- Experience in or exposure to analytics supporting AFC, AML, or compliance risk management.
Technical Knowledge
- Proficiency in Python and/or R for data science and model validation activities.
- Practical knowledge of data wrangling and machine learning libraries such as Pandas, TensorFlow, Keras, or Scikit-learn.
- Experience with SQL and data visualization tools such as Qlik is advantageous.
- Comfortable working with structured and unstructured data across distributed databases.
- Familiarity with natural language processing, network link analysis, and model validation best practices.
