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Job Description
- 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
- 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
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