Responsibilities

📍Universe Risk Management: Conduct data analysis and modeling across key domains such as KYC, payments, credit, and exchange operations. Analyze user behavior and patterns to identify risk indicators and inform decision-making 📍Personalized Services & Anomaly Detection: Leverage our petabyte-scale data warehouse to perform in-depth user analysis. Build personalized services and develop automated systems for detecting abnormal user activity 📍Blockchain-Based Data Insights: Extract and analyze blockchain data to generate predictive insights and tailored recommendations 📍Customer Feedback & Satisfaction Analysis: Apply machine learning techniques to evaluate customer feedback and satisfaction. Provide data-backed insights to guide product and service improvements

Requirements

📍Proven experience in developing machine learning models at scale, from experimentation to deployment 📍Strong understanding of modern machine learning techniques and their mathematical foundations, including classification, recommendation systems, and optimisation methods 📍Hands-on experience working with large-scale datasets; experience with distributed data processing is preferred 📍Proficiency in programming languages such as Python, Java and/or Scala is preferred 📍A Master’s degree or higher in a relevant field (e.g., Computer Science, Statistics, Applied Mathematics) is preferred 📍Experience with deep learning frameworks (e.g., TensorFlow, PyTorch) is a plus 📍Experience in deploying machine learning models into production environments is a strong advantage 📍Bilingual in English and Mandarin is required, to effectively coordinate with overseas partners and stakeholders

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