Principal responsibilities：
• Provide subject matter expertise in the design, development and maintenance of compliance business analytics and models
• Assure that the model deployed in the region are fit-for-purpose by, where required, undertaking testing and/or validation and providing constructive challenge to the Global CA teams
• Deliver analytical work on regional initiatives (data quality reviews and enhancement, model calibration, development and implementation of local deviations/specificities when/where needed)
• Maintain relationships with regional stakeholders providing inputs to improve the performance of the models (EIR, Complex and Major Investigation, Fraud Risk, IMR, etc.)
• Deliver bespoke analysis and MIs helping Compliance and the Business take appropriate risk based decisions
• Support improvements to the systems and data infrastructure supporting deployment of the Compliance models
• Provide technical SME on the various systems and models used in the region

Requirements：
• Degree holder or above in Finance, Mathematics, Risk Management, Statistics, IT or a related field.

Experience：
• Experience in the banking industry, ideally more than 4 years; additional experience in management consulting and/or IT business analysis and project management welcomed
• Previous experience in Financial Crime / Fraud not required but a plus

Skills：
• Team player able to work in a dynamic and multinational culture and cope with high pressure
• Sound judgment and problem solving skills, ability to think laterally
• Strong analytical and statistical skills with the ability to organize and analyse multiple, complex data sets, to draw clear business conclusions and present them clearly to non-scientific stakeholders
• Strong database skills, including working with advanced data sets, advanced database and statistical functions and methods; hands on experience using Python, SAS, SQL, Ali Cloud, Big Data (Hadoop), Visualization tools (Tableau, Qlikview, Spotfire) and Excel (advanced), especially proficient in Python.
• Experience or strong demonstrable interest in recent machine learning techniques