蚂蚁金服Ant International-Fraud Risk Lead-Anext Bank

We are seeking a Business Solutions Engineer with a strong background in financial crime risk systems to drive the design, implementation, and optimization of our KYC (Know Your Customer), Fraud Detection, and Transaction Monitoring (TM) platforms. In this role, you will bridge the gap between business needs and technical solutions — translating regulatory requirements, operational workflows, and fraud risks into scalable, automated system designs. You’ll play a key role in ensuring our digital banking platform remains secure, compliant, and resilient against evolving threats. This is a high-impact position that sits at the intersection of product, technology, compliance, and security — ideal for someone passionate about building intelligent, data-driven risk systems in a fast-moving fintech environment. Lead the analysis and design of end-to-end solutions for KYC onboarding, ongoing customer due diligence, fraud detection, and real-time transaction monitoring systems. Work closely with internal engineering teams to integrate and customize platforms. Collaborate with Compliance, AML, Risk, Operations, and Product teams to gather functional and non-functional requirements. Map current and future-state processes for customer verification, risk scoring, alert investigation, and case management. Ensure system designs meet MAS, FATF, and other regulatory standards for customer identification, suspicious transaction reporting, and fraud prevention. Own end-to-end testing (SIT, UAT, production rollout) of new features and system enhancements. Validate detection efficacy, system performance, and integration with core banking and payment platforms.

Unlike traditional bank AML environment, you would have the chance to work and experience how professional AML works in Ant Bank Hong Kong, the second largest technology based digital bank in Hong Kong and also to join the enegetic AML professional team under the market leading global financial group. Job Responsibilities: 1) Conduct Transactional Monitoring, Know-Your-Customer (KYC), Enhance Due Diligence (EDD) and/or name screening for onboarding, periodic and trigger review on bank customers / account opening applicants within the designated Service Level Agreements before escalatoin to MLRO and/or team lead, if needed. 2) Identify and conduct investigation on suspicious transactions which might relate to sanctioned individuals, money laundering or terrorist financing and prepare the investigation and/or due diligence review report on the risk associated during the end to end investigation / due diligence review process of the Bank. 3) Maintain proper AML/CFT KYC documentations and tracking logs for review and audit trial purpose. 4) Prepare documents for internal / external examination and audit review. 5) Assist the Bank's senior management, MLRO, and the team lead in their oversight and compliance with the Group and the Bank's internal policies and external regulations of Hong Kong. 6) Closely work with relevant stakeholders of the Group and the Bank on ad-hoc projects, such as without limitation, ongoing bank side AML/CFT operations control tasks, as assigned by the Bank MLRO and the team lead. 7) Provide staff training on AML/CFT related topics, policies and procedures.

1、Own and manage the venture risk portfolio, ensuring comprehensive oversight of all platform risks. 2、Lead risk project, conduct in-depth fraud analysis to identify potential threats and vulnerabilities in a timely manner, come up with risk strategies to protect the platform. 3、Collaborate with cross-functional teams, including security/risk stakeholders, commercial, legal, customer care and other operations, to develop and implement risk mitigation strategies or investigate and respond to regulator inquiries on risk-related activities 4、Perform other ad-hoc tasks related to fraud operations

● 岗位职责 主导搭建并迭代全业务线风控与反作弊体系，设计多场景策略框架，保障数据真实和公司利益 分析爬虫、虚假交易、账号作弊、刷量薅羊毛等风险特征，输出并落地风控策略，持续优化拦截率与误判率 搭建实时风险监测体系，及时发现新型作弊手段，主导重大风险应急处置，降低业务损失 协同研发、运营等跨团队推动风控工具/引擎落地，输出风控知识，提升团队风险防控意识 ● 任职资格 计算机、统计学、数学等相关专业，本科及以上学历，3 年及以上风控反作弊经验 扎实数据分析能力，熟练使用 SQL 进行数据查询与清洗，精通 Python（Pandas、NumPy、Scikit-learn 等库）开展特征工程与模型开发 熟悉风控规则引擎（如 URule、Drools）的使用与配置，能将业务规则转化为可落地的风控策略 熟悉 CDN/WAF、设备指纹、浏览器指纹等反爬技术及对抗策略，了解常见爬虫攻击原理与防御逻辑 熟练使用逻辑回归、决策树、随机森林、XGBoost/LightGBM 等风控常用模型，理解模型训练、评估与线上推理全流程 具备敏锐的风险洞察力与逻辑分析能力，优秀的跨团队协作与项目推动能力，能够在高压环境下快速响应并解决复杂风险问题 ● 加分项（选填） 有社区、订阅场景反作弊经验优先 Job Summary We are seeking a highly data mining and technically proficient Anti-Fraud Engineer to join our Risk Control team. In this role, you will be at the forefront of our defense system, designing scalable frameworks to combat sophisticated threats such as bot attacks, fraudulent transactions, and incentive abuse. You will leverage data science, rule engines, and adversarial technologies to safeguard our ecosy Job Responsibilities System Architecture: Lead the end-to-end design and iteration of the company-wide risk control and anti-fraud framework. Architect multi-scenario strategies to safeguard data integrity and corporate interests. Risk Mitigation: Analyze behavioral signatures of risks such as web crawlers, fraudulent transactions, account abuse, and incentive scalping. Develop and deploy targeted strategies to continuously optimize detection precision and minimize false positive/negative rates. Real-time Monitoring & Response: Build real-time risk monitoring systems to identify emerging fraud patterns. Spearhead emergency response efforts for major risk incidents to minimize business losses. Cross-functional Collaboration: Partner with R&D, Operations, and other cross-functional teams to implement risk engines and tools. Disseminate expertise to enhance overall risk awareness across the organization. Job Requirements Educational Background: Bachelor’s degree or above in Computer Science, Statistics, Mathematics, or a related field, with 3+ years of professional experience in risk control and anti-fraud. Data Proficiency: Strong data analysis skills with proficiency in SQL for data extraction and cleaning. Expert in Python (Pandas, NumPy, Scikit-learn) for advanced feature engineering and model development. Rule Engine Expertise: Familiar with the configuration and deployment of risk rule engines (e.g., URule, Drools), with the ability to translate complex business logic into executable technical strategies. Adversarial Defense: Well-versed in anti-crawling technologies and adversarial countermeasures, including CDN/WAF, device fingerprinting, and browser fingerprinting; deep understanding of crawler attack vectors and defense mechanisms. Machine Learning: Hands-on experience with mainstream risk models (e.g., Logistic Regression, Decision Trees, Random Forest, XGBoost/LightGBM) and a thorough understanding of the full lifecycle: training, evaluation, and online inference. Soft Skills: Acute risk insight and logical reasoning. Excellent cross-team collaboration and project management skills, with the ability to resolve complex issues under high-pressure environments. Preferred