Senior Data Scientist, Algorithm (Lending & Onboarding)

Proudly founded in Melbourne, we have a team of over 2,300 of the brightest and most innovative people in tech across 27 offices around the globe. Valued at US$11 billion and backed by world-leading investors including T. Rowe Price, Visa, Mastercard, Robinhood Ventures, Sequoia, Salesforce Ventures, DST Global, and...

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. You move fast with good judgment, dig deep with curiosity, and make decisions ...

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 tha...

As a Senior Data Scientist, you will tackle challenging risk problems across credit and fraud (e.g., account takeover), and help build data-driven decision systems that deliver meaningful business impact. You will be responsible for translating business problems into analytical frameworks, strategies, models, and scalable data solutions.
Build real-time ML models to protect Airwallex customers and platform assets, such as Account Takeover prevention and fraud decisioning
Develop credit risk models and analytical frameworks to assess merchant risk and support the growth of Airwallex’s lending business
Translate business requirements into analytical, modeling, and strategy problems across fraud, credit, onboarding, and related risk domains
Design performance monitoring, metrics frameworks, and decision-support tools to improve risk visibility and decision quality
Partner with Product, Engineering, Operations, and other cross-functional teams to turn data, models, and insights into production strategies and measurable business impact

We're looking for people who meet the minimum qualifications for this role. The preferred qualifications are great to have, but are not mandatory.
3+ years of experience in analytics, data science, risk strategy, or a related quantitative role
Bachelor’s degree or above in a quantitative field such as Statistics, Mathematics, Economics, Computer Science, Engineering, or a related discipline
Proficient in Python and SQL
Strong problem-solving skills and experience working with large datasets
Experience partnering with cross-functional stakeholders to solve business problems
Experience in credit, fraud, or related risk domains
Hands-on experience in model development, validation, or monitoring
Experience designing risk rules, decision strategies, or performance monitoring frameworks