Work in a team of financial supervisors and data scientists to enhance the use of data analytics to improve supervisory outcomes for Money Laundering/Terrorism-Financing (ML/TF) risks, including deploying machine learning/artificial intelligence to detect and prioritise anomalous networks and behaviours for supervisory scrutiny.
Participate in onsite and offsite supervision work, including to execute these analytics methods; and conduct quality assurance and modifications, to improve efficacy of supervisory analytics.
Experience in the use of data analytics, preferably in the financial sector or ML/TF risk management
Familiarity with the use of machine learning/artificial intelligence and possess some coding skills.
Experience in AML/CFT risk management or compliance.
Strong analysis, communication and stakeholder engagement skills.