Key Responsibilities:

• Conduct research on advanced risk control and anti-fraud techniques, including but not limited to machine learning, big data analysis, and graph/network algorithms.

• Collaborate with data engineers and analysts to mine risk patterns from large datasets.

• Support the integration and deployment of risk control solutions with business systems, ensuring seamless and stable operation.

• Work with product managers and business stakeholders to understand risk requirements and translate them into technical solutions.

• Maintain and update documentation for design, development, and deployment processes.

• Stay updated on industry trends, compliance requirements, and best practices in risk management technology.

Requirements:

• 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.