Payment Risk Algorithm Engineer-Risk Control

1. Combine e-commerce and payment data to develop and optimize fraud cash-out models, payment credit scores, user portraits and other models 2. Build machine learning models for each business link, and be responsible for model deployment, application, maintenance, monitoring and upgrade iterations 3. Promote user behavior sequence, consumption power, fraud feature mining, and evaluate and verify data mining results 4. Responsible for optimizing the modeling process, improving model development and deployment efficiency, and reducing model maintenance costs 5. Researching the practice and application of cutting-edge machine learning algorithms in the field.

1. Bachelor degree or above in mathematics or computer science, solid foundation in computer algorithms, familiar with basic theories of machine learning 2. Proficient in modeling languages such as Python/Java/Scala, and proficient in using data statistics tools such as SQL/Hive/Spark/Flink 3. Proficient in common statistical learning methods such as LR and GBDT, familiar with multi-objective learning, deep learning, online learning algorithms, good coding habits and engineering optimization capabilities 4. More than 2 years of work experience in Internet data mining or machine learning 5. Natural language processing, graph mining, and fraud detection are preferred experience in credit scoring and payment risk control is preferred.