UOB

VP, AML Risk Analytics & Modelling , Group Compliance

UOB
BusinessCentral Region (City Area)Full-time1 months ago

About the role

AI summarised

The VP, AML Risk Analytics & Modelling role is a senior compliance position at a bank, responsible for leading the development and implementation of AML risk analytics and modelling frameworks to detect and prevent financial crime.

BusinessFull-timeGeneral

Key Responsibilities

  • Lead the development and enhancement of AML risk analytics and modelling frameworks.
  • Design and implement advanced analytical models for transaction monitoring and suspicious activity detection.
  • Oversee the validation and tuning of AML models to ensure effectiveness and regulatory compliance.
  • Collaborate with business units and technology teams to integrate analytics into AML systems.
  • Provide strategic insights and recommendations to senior management on AML risk trends.
  • Manage a team of data scientists and analysts to deliver high-quality analytics solutions.
  • Ensure adherence to regulatory requirements and industry best practices in AML modelling.
  • Drive innovation in AML analytics through research and adoption of new technologies.

Requirements

  • Bachelor's or Master's degree in a quantitative field such as Statistics, Mathematics, Economics, or Data Science.
  • Minimum 10 years of experience in AML risk analytics, modelling, or related fields within banking or financial services.
  • Strong expertise in statistical modelling, machine learning, and data mining techniques.
  • Proficiency in programming languages such as Python, R, or SQL.
  • Experience with AML transaction monitoring systems and regulatory reporting.
  • Excellent leadership and team management skills.
  • Strong understanding of AML regulations and guidelines (e.g., MAS, FATF).
  • Ability to communicate complex analytical concepts to non-technical stakeholders.
  • Proven track record of developing and deploying risk models in a production environment.
  • Certification in AML (e.g., CAMS) is preferred.