Anti-Fraud Payments Risk Analyst 支付反詐欺風險分析師

About Hytech Hytech is a management consulting company headquartered in Australia and Singapore, focusing on providing digital transformation solutions for the fintech and Financial Services industries. Our services cover multiple areas such as back-office operation support, Human Resource Planning, payment systems, and risk control, committed to providing comprehensive and professional service support to clients. With a team of over 2,000 professionals worldwide, we have deep industry insights and localization implementation capabilities to ensure efficient business progress while complying with local regulations. Hytech always focuses on mid- and back-end solutions, without involving any front-end or transaction-related businesses, continuously helping customers achieve secure, compliant, and sustainable digital transformation. Position Summary We are looking for a highly analytical Anti-Fraud Payments Risk Analyst to join our Payments Risk Analysis team. This role is ideal for candidates with backgrounds in Business Intelligence, Data Analytics, Risk Analytics, FinTech, Payments, Banking, or Fraud Analytics who enjoy using data to identify unusual patterns, investigate business problems, and turn analytical findings into actionable recommendations. Rather than focusing on day-to-day fraud operations, this role is primarily data and analysis driven. You will work with large transactional datasets, monitor business and risk indicators, investigate abnormal trends, develop dashboards and monitoring frameworks, evaluate detection rules, and support the development of data-driven risk controls. Prior fraud experience is not mandatory Candidates with strong BI or Data Analytics backgrounds who are interested in developing expertise in Payments Risk and Fraud Analytics are highly encouraged to apply. You will work closely with Risk Operations, Payments, Product, Engineering, Business Intelligence, Data, Compliance and Business teams to improve our understanding of customer and transaction behaviour and continuously strengthen our payment risk framework. Key Responsibilities: Data Analysis & Pattern Identification • Analyze large volumes of payment, transaction and customer behavioural data. • Identify unusual patterns, trends, anomalies and potential risk indicators. • Perform deep-dive analysis to understand what happened, why it happened and what actions should be taken. • Translate analytical findings into clear business and risk recommendations. Business & Risk Monitoring • Monitor key business and risk metrics across multiple brands and payment channels. • Investigate unusual spikes, drops or changes in transaction and alert volumes. • Conduct root cause analysis and determine whether changes are driven by customer behaviour, business changes, system issues or emerging risks. • Develop appropriate monitoring indicators and early-warning mechanisms. • Conduct analytical investigations into areas such as: Chargeback trends and Payment abuse or arbitrage Dashboard & reporting Development Develop monitoring metrics and management reporting. Improve data visualization and make complex analytical findings easy for business stakeholders to understand. Identify opportunities to automate recurring reporting and monitoring activities. Risk Rule & Performance Analytics • Analyze the performance of existing risk and fraud detection rules. • Evaluate detection coverage, accuracy, True Positive / False Positive trends and alert volumes. • Identify opportunities to improve thresholds and detection logic. • Support testing and validation before and after rule implementation. • Measure the business impact and effectiveness of newly implemented controls. • Prepare regular analytical reports covering risk trends, rule performance and key business observations. • Present findings and recommendations to management and cross-functional stakeholders. Qualifications & Requirements • Bachelor's degree in Business Analytics, Data Analytics, Computer Science, Information Systems, Statistics, Mathematics, Finance, Economics, or related fields. • Experience in one or more of the following: Business Intelligence, Data Analytics, Risk Analytics, Product Analytics, Fraud Analytics, FinTech, Banking, Payments, Brokerage or other analytical roles. • Strong analytical and problem-solving skills. • Ability to work with large datasets and identify meaningful patterns or anomalies. • Proficiency in SQL for data querying and analysis. • Experience with Python for data analysis, automation or scripting. • Some experience with Power BI, Tableau or equivalent BI / visualization tools. • Strong Excel skills. • Ability to translate data findings into practical business recommendations. • Good communication skills and ability to explain analytical findings to non-technical stakeholders.