Job Responsibilities
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Conduct data analysis, feature engineering, and feature extraction for data within the financial industry
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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
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Maintain and optimize data pipelines, enhancing existing solutions through pre- and postprocessing improvements, fine-tuning, performance evaluation, visualization, and testing
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Collaborate with cross-functional teams to identify and address customer needs and aspirations
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Proactively resolve ambiguity and tackle technical issues, driving innovation and efficiency in processes
Job Requirements
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Bachelor's or Master's degree in Computer Science, Information Technology, Data Science, Statistics, or related fields
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Proficiency in at least one machine learning development framework, such as PyTorch, Keras, or TensorFlow, with hands-on experience in environment control
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Experience with programming, monitoring, visualization and project collaboration tools, including Python, VSCode, Conda, Git, and MySQL
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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
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Interest in areas such as anomaly detection, federated learning, transfer learning, self-supervised learning, or uncertainty quantification
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Knowledge in LLM is a plus
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A passion for coding, programming, innovation, and problem-solving
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A keen interest in anti-money laundering practices and regulatory compliance
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Proficient in written and spoken Chinese (Cantonese or Mandarin); fluency in English is a plus
If you are interested in the position, please send your resume with your current and expected salary to [email protected].
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Personal data collected will be used for recruitment purposes only.
FULL TIME
Mid-Level
4/19/2026
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