岗位概述
协助搭建和迭代业务线风控与反作弊体系，通过数据分析、特征工程和模型建设保障平台数据真实性与业务安全。
本岗位为 2026 年暑期实习，全职实习时长 5 个月以上。实习期间表现优秀者，将有机会获得留用。
职责描述
- 协助搭建和迭代业务线风控与反作弊体系，配合设计多场景策略框架，辅助保障数据真实和公司利益
- 协助分析爬虫、虚假交易、账号作弊、刷量等风险特征，参与风控策略的输出与落地，辅助优化拦截率与误判率
- 协助搭建实时风险监测相关模块，配合发现新型作弊手段，参与重大风险应急处置
- 参与特征工程、模型（如 XGBoost、决策树、随机森林）的辅助开发、调试与优化工作
- 协同研发、运营等跨团队，推动风控工具/引擎落地，整理风控相关知识文档
任职资格
- 计算机、统计学、数学、数据科学等相关专业，本科及以上学历
- 具备基础数据分析能力，熟练使用 SQL 进行数据查询与清洗，掌握 Python（Pandas、NumPy、Scikit-learn 等库）
- 了解风控、反作弊相关概念，对爬虫、账号作弊、刷量等场景有基本认知
- 具备良好的逻辑分析能力、学习能力和团队协作精神
加分项
- 了解常用风控算法（决策树、随机森林、XGBoost 等），有相关实践经验
- 有特征工程或简单模型开发经验
- 有风控或反作弊相关项目/实习经验
▸ Overview
You'll help build and iterate risk control and anti-fraud systems, using data analysis, feature engineering, and machine learning to protect platform integrity across business lines.
This is a full-time summer 2026 internship (5+ months). Strong performers will be considered for a return offer.
▸ Responsibilities
- Support the development and iteration of risk control and anti-fraud frameworks across multiple business scenarios
- Analyze fraud patterns (scraping, fake transactions, account abuse, bonus farming, etc.); contribute to strategy deployment to improve intercept rates and reduce false positives
- Help build real-time risk monitoring modules; assist with incident response for emerging fraud vectors
- Participate in feature engineering and model development/optimization (XGBoost, Decision Trees, Random Forests)
- Collaborate cross-functionally to deploy risk tools and maintain internal knowledge documentation
▸ Qualifications
- Bachelor's degree or above in CS, Statistics, Mathematics, Data Science, or a related field
- Proficient in SQL for data querying and cleaning; solid Python skills (Pandas, NumPy, Scikit-learn)
- Basic familiarity with risk control and anti-fraud concepts
- Strong logical thinking, quick learner, and collaborative team player
▸ Bonus Points
- Hands-on experience with risk algorithms (Decision Trees, Random Forests, XGBoost, etc.)
- Experience with feature engineering or basic model development
- Prior internship or project experience in risk control or anti-fraud