Job Scope:

  • 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.  

Requirements:

  • 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

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