Job Description:

  • Responsible for developing Machine learning solutions for identifying and preventing various fraudulent activities across different markets
  • Understand the business requirements and convert them into quantifiable key metrics for technical solution
  • Analyze massive user behavioral data to mine abnormal behavior patterns and work with business stakeholders on identifying fraud trends
  • Develop and improve fraud detection models with the state-of-the-art techniques in big data and machine learning, such as deep learning, graph neural networks
  • Build data pipeline to enable scalable and real-time fraud detection
  • Analyse/test the model’s effectiveness in fraud prevention
  • Deploy the model in production and continuously monitor/update model performance
  • Experience or knowledge working on fraud related products or e-commerce industry will be an advantage but not a prerequisite

Minimum Requirements

  • Bachelor’s Degree in Computer Science or related technical discipline
  • Experience in common Machine Learning frameworks such as scikit-learn, Tensorflow, PyTorch
  • Good coding skills in one or more programming languages, e.g. Python, Golang

Preferred Requirements

  • Experience in building and optimizing big data pipelines
  • Experience in developing and deploying real-time machine learning or other web backend services
  • Experience in deep learning model serving frameworks, such as TensorRT

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