• Conduct data analysis, feature engineering, and feature extraction for data within the financial industry
• Develop and implement cutting-edge machine learning algorithms focused on graph learning and time series analysis for applications such as transaction monitoring, anti-money laundering, and cryptocurrency analysis
• Maintain and optimize data pipelines, enhancing existing solutions through pre- and post-processing improvements, fine-tuning, performance evaluation, visualization, and testing
• Collaborate with cross-functional teams to identify and address customer needs and aspirations
• Proactively resolve ambiguity and tackle technical issues, driving innovation and efficiency in processes
  
  
  

• Bachelor’s or Master’s degree in Computer Science, Information Technology, Data Science, Statistics, or related fields
• Proficiency in at least one machine learning development framework, such as PyTorch, Keras, or TensorFlow, with hands-on experience in environment control
• Experience with programming, monitoring, visualization and project collaboration tools, including Python, VSCode, Conda, Git, and MySQL
• Knowledge of statistical machine learning and deep learning, particularly the models for graph and/or time series data, such as knowledge graph, spatial-temporal graph, and multivariate time series
• Interest in areas such as anomaly detection, federated learning, transfer learning, self-supervised learning, or uncertainty quantification
• Knowledge in LLM is a plus
• A passion for coding, programming, innovation, and problem-solving
• A keen interest in anti-money laundering practices and regulatory compliance
• Proficient in written and spoken Chinese (Cantonese or Mandarin); fluency in English is a plus

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