Senior Data Scientist, Analytics (Risk & Fraud)

Airwallex
SG - SingaporePosted 24 March 2026

Job Description

Senior Data Scientist, Analytics (Risk & Fraud) ABOUT AIRWALLEX Airwallex is the only unified payments and financial platform for global businesses. Powered by our unique combination of proprietary infrastructure and software, we empower over 200,000 businesses worldwide – including Brex, Rippling, Navan, Qantas, SHEIN and many more – with fully integrated solutions to manage everything from business accounts, payments, spend management and treasury, to embedded finance at a global scale. Proudly founded in Melbourne, we have a team of over 2,000 of the brightest and most innovative people in tech across 26 offices around the globe. Valued at US$8 billion and backed by world-leading investors including T. Rowe Price, Visa, Mastercard, Robinhood Ventures, Sequoia, Salesforce Ventures, DST Global, and Lone Pine Capital, Airwallex is leading the charge in building the global payments and financial platform of the future. If you’re ready to do the most ambitious work of your career, join us. ATTRIBUTES WE VALUE We hire successful builders with founder-like energy who want real impact, accelerated learning, and true ownership. You bring strong role-related expertise and sharp thinking, and you’re motivated by our mission and operating principles https://www.airwallex.com/us/operating-principles. You move fast with good judgment, dig deep with curiosity, and make decisions from first principles, balancing speed and rigor. You're humble and collaborative; turn zero‑to‑one ideas into real products, and you “get stuff done” end-to-end. You use AI to work smarter and solve problems faster. Here, you’ll tackle complex, high‑visibility problems with exceptional teammates and grow your career as we build the future of global banking. If that sounds like you, let’s build what’s next. ABOUT THE TEAM The Product team at Airwallex is a group of passionate builders and problem-solvers who are obsessed with crafting customer-centric solutions that empower businesses to operate anywhere, anytime. We combine technical expertise with a deep understanding of our customers' needs to design and build unified, intuitive, and scalable products. As a team, we thrive in a collaborative and fast-paced environment, constantly iterating and pushing boundaries to deliver exceptional product experiences. WHAT YOU’LL DO Airwallex is building a centralised risk platform that will harness advanced analytics and machine learning techniques to enable real-time decisioning across a diverse range of product lines and platforms. The risk product domain is responsible for building the platforms, engines & case management whilst also delivering the risk models so you will be involved in crafting the full end-to-end risk capability. This role will work on building out Airwallex’s risk product domain focusing on analyzing the compliance impact on transactions as well as delivering a financial crime detection and prevention solution. You will be responsible for conducting risk analysis on transaction level and merchant level, developing risk detection framework, and empowering business. RESPONSIBILITIES: - Craft and refine risk strategies which include defining risk controls, customer experience and operational workflows, with emphasis on minimizing the impact on customers, our brand and organizational critical metrics - Use data driven insights to seize opportunity, measure performance, and determine what is working and what is not working. Monitor performance of existing & new solutions and optimize to ensure desired results - Communicate concise and actionable business strategies and present new strategy recommendations to senior management for approval - Collaborate with partners in Platform, Operations and other internal teams, as well as external partners like data vendors to formulate and execute fraud risk solutions WHO YOU ARE We're looking for people who meet the minimum qualifications for this role. The preferred qualifications are great to hav ... (truncated, view full listing at source)
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