- Provide data-driven insights of the behavior and intentions of users who violate or abuse the system and policies of Shopee.
- Design and implement end-to-end machine learning or statistical models for the following areas:
- Preemptive or responsive fraud detection with high interpretability
- Realtime identity verification for the Know-Your-Customer processes of various Shopee’s products
- Work cross-functionally with business, operation, and engineering teams during the whole life-cycle of security products, from problem formulation, solution design, implementation, maintenance and improvement.
- Minimum Bachelor’s degree from related disciplines.
- Self-motivated, independent and fast learner. Teamplayer who loves to share with and learn from others.
- 2 years working experience with a programming language such as Python or C++
- Experience on SQL, Spark, Kafka
- Familiar with traditional machine learning framework such as sk-learn, xgboost, LightGBM, CatBoost or modern deep learning framework like TensorFlow and PyTorch
- Experience on designing and implementing industry-level anti-fraud system is a plus
- Experience on developing OCR or face recognition model is a plus
- Experience on model compression or quantization for on-device inference is a plus