Risk Analyst

Join to apply for the Risk Analyst role at Reap About Reap Reap is a global financial technology company headquartered in Hong Kong with employees across multiple countries. We enable financial connectivity and access for businesses worldwide by combining traditional finance with stablecoins for efficient money movement. Through our stablecoin-powered corporate cards, payments, and expense management tools, we streamline financial operations and help businesses scale. Our APIs enable businesses to integrate stablecoin-enabled finance into their own products and services—from issuing Visa cards to facilitating cross-border payments. Backed by leading investors including Index Ventures and HashKey Capital, Reap is building the future of borderless, stablecoin-enabled finance. Why Reap? At Reap, we’re building financial infrastructure that businesses can trust. This role sits at the intersection of fraud prevention, risk management and data analytics, giving you the chance to shape how Reap scales securely in the worlds of global payments and Web3. As we expand across new markets and products, the complexity of our risk landscape grows too—giving you the chance to take on new challenges, lead initiatives, and make your mark on the future of secure fintech. Your Mission Awaits Your mission is to strengthen Reap’s payments infrastructure by driving smarter risk decisions through data and analytics. You will play a pivotal role in assessing risks across our card transaction ecosystem, identifying emerging patterns, and shaping strategies that keep our platform secure and resilient. By leveraging data-driven insights, advanced risk tools, and cross-functional collaboration, you will help build frameworks that balance security with customer experience. As Reap expands into new markets and products, you will ensure our risk strategies evolve in step—enabling us to scale with confidence in the fast-moving world of global payments and Web3. You Will Champion data-driven risk decision-making, translating analytical insights into practical strategies that strengthen our overall risk framework. Shape Reap’s risk strategy by analyzing transaction and portfolio data to uncover emerging patterns, vulnerabilities, and evolving market risks. Elevate our defenses by developing smarter policies, thresholds, and risk models that balance security, compliance, and customer experience. Build and refine dashboards, models, and detection tools that keep us one step ahead of fraudsters. Lead deep-dive investigations into high-risk behaviors, identifying root causes and shaping long-term preventive measures. Contribute to innovation by leveraging modern analytical techniques, including machine learning and anomaly detection, to strengthen fraud monitoring. Analyze transaction data to detect patterns indicative of fraud, investigating anomalies, and taking immediate action to prevent losses. Collaborate cross-functionally with product, compliance, and engineering teams to ensure fraud insights influence product innovation and risk frameworks. Your Superpowers Minimum of 3-5 years of experience in fraud, risk or data analytics teams within the fintech or financial services industry. Deep understanding of credit card networks and card transaction processing. Strong analytical and problem-solving skills, with hands-on experience in building risk-oriented data products. Exceptional attention to detail, with a proven ability to identify subtle indicators of fraud within large datasets. Strong communication skills, capable of articulating complex fraud patterns and risk mitigation strategies to both technical and non-technical audiences. Strong analytical skills and proficiency in statistical modeling, data analysis, and risk assessment techniques. Sound judgment, strategic thinking, and the ability to make informed decisions in a fast-paced, dynamic environment. A proactive approach to identifying potential vulnerabilities and implementing preventive measures. Ability to work independently in a hybrid/remote environment. Nice to Have Experience building and validating machine learning models for fraud detection, anomaly detection, or risk scoring. Familiarity with big data technologies (e.g., Spark, Hive, or cloud-based data warehouses like Snowflake/BigQuery) to analyze large-scale transaction datasets. Knowledge of network analysis or graph-based techniques for uncovering relationships and fraud rings within complex data structures. Why You\'ll Love It Here A high-impact role in a rapidly growing fintech startup Flexible hybrid/remote work environment with a global, collaborative team Insurance coverage after probation Use of AI tools at work — and the space to learn, experiment, and grow with them A culture of innovation, inclusion, and continuous learning After submitting your application, please check your inbox for a confirmation email. If you don’t see it, kindly check your spam or junk folder and adjust your settings to ensure future communication reaches your inbox. Note: Seniority level, employment type, and job function are listed for reference. #J-18808-Ljbffr