Work on risk model development for retail and SME finance products such as consumer lending, personal finance, small and medium-sized enterprises loan and so on
Build models and tools for credit and fraud risk identification in various aspects. For example, credit risk modelling, income estimation, customer information verification, anti cash-out, non-starter detection, account take over and so on
Maintain business operations for credit and fraud risk products in various aspects. For example, conduct product backtesting, pipeline stability check, and build relevant monitor dashboards and so on
Collaborate closely with the risk policy and business team. Translate business need and insight into machine learning models and product solutions.
Research model methodology and data mining techniques to improve model performance
Requirements
Bachelor's degree in Machine Learning, Business Analytics, Information Technology, Finance, Economics, Statistics, Mathematics, or a related field. Master's and PhD degree are preferred.
1-5 years relevant credit or anti-fraud model development experience
Experienced with data mining and feature engineering from massive raw data especially the alternative credit data
Solid understanding and hands on experience of machine learning models such as boosting trees, regression models and good sense in feature engineering
Good coding skill using SQL, Spark and Python
Eager to learn new things and has passion in work
Take responsibility, team oriented, result oriented, customer oriented and self driven
Experience in network analysis, search and recommendation system and other machine learning field is a plus
