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
