Project Overview

Our client is working with a large global bank to support a data analytics initiative focused on enhancing the bank’s existing tool used to detect suspicious activity and potential financial crime. The client is seeking a Cantonese-speaker with financial crime expertise to support improvements to this tool, with a focus on refining the underlying data inputs and detection logic to strengthen the effectiveness of the current model.

The role will be based in Hong Kong and will follow a hybrid working model (75% on-site). The consultant will support the setup and early structuring of the programme, helping the team understand the types of financial crime risks being targeted and the data required to improve the detection capability.

What You Will Be Doing

• Support the setup and early-stage structuring of a financial crime data analytics programme
• Work with stakeholders to understand different types of financial crime and how these can be detected using data and analytics tools
• Contribute to enhancing the bank’s existing tool used to detect suspicious activity and potential financial crime
• Help identify and define the relevant data elements required to improve detection models
• Collaborate with stakeholders across financial crime, data, and technology teams
• Work as part of a team of four members delivering the project
• Provide project support through effective communication, coordination and execution of assigned deliverables

Your Background

• 5–10 years of professional experience
• Experience working in the financial crime domain (e.g. AML, fraud, transaction monitoring or related areas)
• Fluent Cantonese speaker
• Experience working on project-based work or programme delivery
• Strong communication and stakeholder engagement skills
• Exposure to data analytics initiatives or projects involving data-driven detection models
• Familiarity with large datasets, data elements, or data architecture/storage concepts is a nice to have
• Experience in banking, fintech, payments or other industries with financial crime exposure is acceptable