Data Scientist, Analytics

• Own a real-world project stream end-to-end, such as syndicate detection, user behavior sequencing, market manipulation detection, or feature discovery
• Process and analyze billions of records using PySpark, Hive, and Trino
• Develop robust SQL pipelines for feature engineering and validation
• Build, evaluate, and iterate on machine learning models
• Translate model performance into business metrics such as detection rate, false-positive rate, and latency
• Work with the Risk AI DS team on risk-detection models using large-scale user behavior, fund-flow, and market data

• Currently pursuing a degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, or a related quantitative field
• Current university students and recent graduates may apply
• Strong foundation in machine learning concepts
• Proficiency in Python and SQL
• Familiarity with database management systems such as MySQL, PostgreSQL, SQL Server, or MongoDB
• Comfortable working with large-scale datasets
• Experience with Apache Spark is a plus
• Proficient in leveraging AI coding agents, such as Claude Code or Cursor
• Proactive and detail-oriented, with a strong instinct for investigating data anomalies and identifying root causes
• Clear and effective English communication skills, with the ability to articulate technical findings and collaborate effectively

• Competitive salary and company benefits
• Work-from-home arrangement (the arrangement may vary depending on the work nature of the business team)
• Opportunities for career growth and continuous learning
• Networking and development opportunities
• Flat organizational structure
• Autonomy in an innovative environment