Campaign Risk‑Control Strategy Specialist

We are looking for a Risk Strategy Specialist to design and operate risk control strategies for marketing and growth campaigns. This role will focus on high-risk scenarios such as user acquisition, promotional campaigns, coupon distribution, referral programs, and activation campaigns. You will use data-driven methods to identify and prevent fraudulent behaviors, incentive abuse, fake traffic, and other forms of marketing exploitation, while helping build scalable risk control capabilities across the platform. Design anti-fraud and anti-abuse strategies for marketing campaigns, including major promotions, coupon campaigns, discount programs, referral campaigns, and user growth initiatives. Build end-to-end risk control mechanisms covering pre-campaign budget monitoring, real-time interception during campaigns, and post-campaign offline audits. Analyze user behavior, transaction behavior, device signals, account patterns, and campaign data to identify fraud patterns and abuse tactics. Extract and maintain risk features, labels, and rules based on data analysis and fraud investigations. Monitor campaign risks, evaluate strategy performance, and continuously optimize risk rules to balance user experience, campaign efficiency, and risk exposure. Work closely with product, operations, engineering, data science, and business teams to convert risk strategies into product features, automated rules, models, or risk engine capabilities. Support the evolution of risk infrastructure, including risk engines, automated decisioning tools, and AI-assisted risk operations. Bachelor's degree or above, preferably in Computer Science, Information Technology, Statistics, Mathematics, or a related field. 5+ years of experience in risk strategy, fraud risk, anti-abuse, risk analytics, or algorithm-related roles. Hands-on experience in marketing risk control, campaign anti-abuse, fake account prevention, batch registration detection, account governance, or similar scenarios. Strong understanding of fraud patterns and adversarial tactics in user acquisition, promotional campaigns, referral programs, and incentive-based growth activities. Strong capability in risk strategy design, risk pattern mining, data analysis, and rule optimization. Proficient in SQL and Python, with the ability to independently conduct data analysis, feature mining, and strategy evaluation. Strong cross-functional collaboration skills, with experience working with product, operations, engineering, and data science teams. Experience with risk engines, automated decisioning systems, machine learning models, or AI-assisted risk operations is a plus.