Responsibility

• Develop predictive and decision models to be deployed in systems.  This includes the analysis of historical data, data cleaning, sampling, variable selection, modeling and performance evaluation.
• Conduct regular validation and monitoring on the performance of decision models for retail portfolios.
• Formulate data driven decision strategies across the customer credit lifecycle including origination, portfolio management and collections.
• Streamline the process and workflow across the customer credit lifecycle. 
• Prepare the user requirement documents and participate in user acceptance tests on decision models.

Requirements:

• Bachelor degree holder or above in Mathematics, Statistics, Risk Management, Computer Science, Science in Investment Science and Finance Analytics ,Engineering or Operations Research.
• Fresh graduate or candidate with 2 years’ working experience in risk analytics or modelling.
• Knowledge of at least one of the following software, SAS, Python, R, Alteryx, Tableau
• Hands-on experience in Python, R or SAS, and familiarity with these software program coding standards and best practices.
• Strong statistical knowledge of the following: Segmentation, Linear and Logistic Regressions, Machine Learning algorithms such as Random Forest and XGBoost
• Knowledge of Generative AI will be an advantage.
• Good communication skill, passionate and energetic
• Good command of written and spoken Chinese and English. Fluent Mandarin will be an advantage