• Conduct research on advanced techniques for risk control and anti-fraud, including but not limited to:
  • Machine learning
  • Big data analysis
  • Graph/network algorithms
• Collaborate with data engineers and analysts to identify risk patterns from large datasets.
• Support the integration and deployment of risk control solutions within business systems, ensuring smooth and stable operations.
• Engage with product managers and business stakeholders to comprehend risk requirements and convert them into technical solutions.
• Maintain and update documentation related to design, development, and deployment processes.
• Stay informed about industry trends, compliance requirements, and best practices in risk management technology.

§ Bachelor’s or Master’s degree in Computer Science, Software Engineering, Information Security, Data Science, or a related field.

§ Solid programming skills in at least one mainstream language (e.g., Java, Python, Scala, C++).

§ Experience in developing risk control, anti-fraud, or real-time monitoring systems is preferred.

§ Familiarity with relevant algorithms and modeling techniques, such as machine learning, statistical analysis, and graph theory.

§ Proficient in data processing and analysis tools and frameworks, including big data platforms like Hadoop, Spark, or Flink.

§ Strong analytical and problem-solving abilities, with high attention to detail.

§ Good communication and collaboration skills, able to work effectively in cross-functional teams.

§ Knowledge of financial industry risk control, regulatory compliance, or blockchain technology is a plus.