<p><strong>Key Responsibilities</strong></p><ul><li><p>Conduct research on advanced risk control and anti-fraud techniques, including but not limited to machine learning, big data analysis, and graph/network algorithms.</p></li><li><p>Collaborate with data engineers and analysts to mine risk patterns from large datasets.</p></li><li><p>Support the integration and deployment of risk control solutions with business systems, ensuring seamless and stable operation.</p></li><li><p>Work with product managers and business stakeholders to understand risk requirements and translate them into technical solutions.</p></li><li><p>Maintain and update documentation for design, development, and deployment processes.</p></li><li><p>Stay updated on industry trends, compliance requirements, and best practices in risk management technology.</p></li></ul><p><strong>Requirements</strong></p><p></p><ul><li><p>Bachelor’s or Master’s degree in Computer Science, Software Engineering, Information Security, Data Science, or a related field.</p></li><li><p>Solid programming skills in at least one mainstream language (e.g., Java, Python, Scala, C++).</p></li><li><p>Experience in developing risk control, anti-fraud, or real-time monitoring systems is preferred.</p></li><li><p>Familiarity with relevant algorithms and modeling techniques, such as machine learning, statistical analysis, and graph theory.</p></li><li><p>Proficient in data processing and analysis tools and frameworks, including big data platforms like Hadoop, Spark, or Flink.</p></li><li><p>Strong analytical and problem-solving abilities, with high attention to detail.</p></li><li><p>Good communication and collaboration skills, able to work effectively in cross-functional teams.</p></li><li><p>Knowledge of financial industry risk control, regulatory compliance, or blockchain technology is a plus.</p></li></ul>