Independently validate Anti-Financial Crime (AFC) models in accordance with the bank's model validation standards, producing comprehensive reports that document findings and actionable recommendations
Evaluate the robustness of model design, development methodology, and data integrity. Conduct thorough reviews of development code to ensure alignment with documented methodologies and results
Review and assess follow-up actions taken by model owners in response to issues identified in prior validations
Communicate validation outcomes clearly and effectively to management and stakeholders, translating technical findings in non-technical language
Collaborate with regional teams to prepare regular reports on model performance for senior management
Actively participate in the enhancement of model validation standards and frameworks
Team contributions
Stay informed on evolving regulatory requirements, industry best practices, and analytical advancements in AFC risk management. Propose updates to model development standards in consultation with the team lead
Assist in the planning and coordination of the model validation calendar
Support initiatives related to systems, infrastructure and databases used for analytic projects
Requirements
Undergraduate degree in a quantitative field, with 5 -8 years of experience in analytics / technology domain, and preferably 2 -3 years of experience in advanced data analytics
Prior experience working on large-scale analytics projects
Experience in or familiarity with analytics related to AFC/AML/compliance risks
Strong ability to communicate complex technical findings clearly and effectively, tailored to both technical and non-technical audiences
Demonstrated capability to manage multiple concurrent projects in a fast-paced environment
Technical skills
Proficiency in Python and / or R for data science, with practical knowledge of data wrangling and machine learning libraries (e.g., Pandas, Keras, Tensorflow, Sklearn)
Proficiency in querying and visualization tools such as SQL and Qlik will be an advantage
Comfortable working with structured and unstructured data and distributed databases
Familiar with natural language processing and network link analysis
Familiar with model development and validation best practices
