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Data Driven Anti-Financial Crime Specialist

1 week ago

Sydney, New South Wales, Australia Macquarie Bank Limited Full time
About the Position

As the Fraud Detection and Analytics Manager at Macquarie Bank Limited, you will have the opportunity to lead the development and implementation of fraud detection strategies for the Credit and Debit Card portfolio. This involves leveraging data analytics, machine learning, and advanced fraud detection technologies to mitigate financial crime risks.

This role is critical in ensuring the security and trustworthiness of Macquarie Bank's financial environment. The successful candidate will work closely with cross-functional teams to identify, assess, and prevent fraudulent activities.

Main Responsibilities
  1. Fraud Detection Frameworks and Tools: Develop and maintain effective fraud detection frameworks and analytical tools to enhance risk management capabilities.
  2. Data Analysis and Optimization: Utilize advanced data techniques to improve fraud detection efficiency and reduce false positives, ensuring timely and accurate alerts.
  3. Cross-Functional Collaboration: Work with Risk, Compliance, Technology, and Operations teams to strengthen fraud prevention strategies and ensure seamless integration across departments.
  4. Emerging Trends and Risks: Monitor emerging fraud trends and implement proactive measures to mitigate evolving risks, maintaining a secure financial environment.
  5. Performance Monitoring and Reporting: Develop and continuously monitor fraud-related dashboards, reports, and KPIs to track performance and mitigation effectiveness, enabling data-driven decision making.
Requirements and Qualifications
  • Expertise in Fraud Detection: 4+ years of experience in fraud detection, risk analytics, or financial crime management in the banking or financial services sector.
  • Technical Skills: Proficiency in data analytics, statistical modeling, and machine learning techniques, as well as experience with fraud detection tools, transaction monitoring systems, and coding languages such as Python, SQL, Tableau, and Power BI.
  • Educational Background: A Bachelor's or Master's degree in Data Analytics, Computer Science, Statistics, or a related field is desirable.