Responsibilities:
1. Responsible for massive data processing, modeling, and analysis reports;
2. Realize risk modeling through researching customer basic information, credit information, behavior logs, and other data;
3. Utilize machine learning to solve problems related to financial technology scenarios, including but not limited to traffic acquisition, risk control, customer relationship maintenance, etc.;
4. Design risk control data collection, integration requirements, build risk control data model data management warehouse and data mart, and explore the implementation of automated risk control platform.
Requirements:
1. Master's degree or above, with relevant work experience in big data analysis and machine learning modeling preferred;
2. Familiar with databases and data analysis tools, proficient in using SQL, Python, R, SAS, etc. for efficient data processing, mining, and analysis;
3. Proficient in the basic principles and applications of machine learning, with a good understanding of common algorithms such as GBDT, XGBoost, RandomForest, logistic regression, etc., and deep learning experience is a plus;
4. Have good logical analysis skills, be good at communication and expression, can withstand fast-paced work pressure, and are willing to constantly learn new knowledge. Excellent English reading and communication skills are a plus.