Senior Data Scientist, Algorithm - Financial Markets
AirwallexUS - San FranciscoPosted 24 March 2026
Tech Stack
Job Description
Senior Data Scientist, Algorithm - Financial Markets
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
As a global team, we span across Australia, China, USA, and Singapore, revolutionizing applied data science, data engineering and platform solutions to support Airwallex's rapid growth. You will collaborate with a diverse range of cross-functional partners, including Product, Engineering, Marketing, Sales, Finance, and more, to tackle complex data problems and shape the future of fintech.
Learn more about the data science team in this blog. https://careers.airwallex.com/blog/data-science-leader/
THE ROLE
- Effectively manage Airwallex’s risk portfolio, delivering actionable insights to shape our overall risk strategy within financial markets
- Apply statistical and/or machine learning models to estimate financial markets risk exposures (including FX, credit, capital, and other product risks), and optimize market forecasting, order routing, fund efficiency, and pricing decisions
- Partner with Product Managers, Traders, Risk, Engineering, and other stakeholders to deliver data-driven recommendations that support commercial and operational objectives
- Clearly present analytical results and insights to cross-functional teams to influence business strategies and decision-making
WHO YOU ARE
We're looking for people who meet the minimum qualifications for this role. The preferred qualifications are great to have, but are not mandatory.
MINIMUM QUALIFICATIONS:
- 5+ years industry experience and an advanced degree (PhD or MS) in a quantitative field (e.g. Statistics, Engineering, Sciences, Computer Science, Economics)
- Strong understanding of financial markets, foreign exchange, and/or dynamic trading systems is a plus
- Experience with communicating the results of analyses to executives and cross-functional teams to influence the strategy
- Expert in data querying languages (e.g. SQL), scripting languages (e.g. Python), and/or statistical/mathematical software (e.g. R), experience in schema design and dimensional data modeling a plus
- Ability to perform statistical analysis and develop machine learning models to drive data-informed decisions
PREFERRED QUALIFICATIONS:
- Experience in technology, financial services, trading ... (truncated, view full listing at source)
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