Staff 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 250,000 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 2,300 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 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. 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.

About the role

• Own and drive the modelling and analysis roadmap for the FX product, identifying high-impact opportunities and prioritising work in collaboration with Product managers.

• Develop and maintain models to forecast and monitor FX rate volatility, providing actionable insights to support trading and execution strategy.

• Apply statistical and/or machine learning models to optimise FX trade execution - focusing on minimising cost, improving routing efficiency and managing market risk exposure.

• Conduct data-driven analyses including but not limited to customer cohort analysis, profitability analysis, and customer segmentation to support commercial decision-making.

• Partner with Product Managers, Traders, Risk, Engineering, and other stakeholders to translate analytical findings into trading and product decisions.

• Clearly communicate analytical insights and recommendations to cross-functional teams to influence business strategies and decision-making.

Location of role: San Francisco

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:

• 7+ 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 environment and/or a high growth environment is advantageous.

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