Staff Data Scientist, Algorithm - Growth

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. 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.

Growth Data Science Team

The Growth Data Science team sits at the center of Airwallex’s growth engine, turning data and AI into a durable competitive advantage. We build and scale advanced solutions—from predictive modeling and personalization to LLM-powered systems, incentive optimization, and causal inference—to unlock step-change growth across the customer lifecycle.

Learn more about the data science team in this blog.

The Role

We’re seeking a Staff Data Scientist to partner closely with the Growth and Marketing teams to design, deploy, and iterate on high-impact data science solutions that drive measurable business outcomes. In this role, you will apply machine learning models to influence how we acquire, engage, and retain customers globally.

Your work will directly shape Airwallex’s growth strategy, influencing how we acquire, engage, and retain customers. You are naturally curious, business-oriented, and have a proven track record of translating data insights into actionable recommendations that strengthen brand presence and accelerate growth.

Why Join Now

You’ll join the Airwallex team during a critical period, where we are building a team that enables both global consistency in process, tooling and methodology and local flexibility and speed in execution. This is a great opportunity to shape the next phase of Airwallex’s growth.

Responsibilities

• Uplevel the data science team by providing technical mentorship, assuming hands-on leadership to resolve complex problems, and setting the vision for longer term direction

• Serve as a strategic thought leader with Marketing, Growth Product, Engineering, and cross-functional teams to inform, influence, support, and execute GTM strategy and investment decisions

• Design and deploy a range of data science solutions—including predictive models, personalization and recommendation systems, LLM-powered applications, incentive optimization frameworks, and causal inference models—to drive measurable business outcomes

• Apply machine learning and/or statistical models to measure causal impact of Marketing initiatives

Qualifications

• 7+ years industry experience and an advanced degree (PhD or MS) in a quantitative field (e.g. Statistics, Engineering, Sciences, Computer Science, Economics)

• Experience with communicating the results of analyses to leadership teams and cross-functional teams to influence the strategy

• Technical mentorship experience with machine learning and experimentation in an industry setting

• Expert in machine learning and statistical modeling to drive data driven growth strategy

• Hands on experience building, deploying, and maintaining machine learning models in production-grade systems (e.g., cloud-based services, real-time and batch pipelines).

• Expert in data querying languages (e.g. SQL), scripting languages (e.g. Python); experience in schema design and dimensional data modeling a plus

• Experience in technology, financial services and/or a high growth environment is advantageous

Applicant Safety Policy: Fraud and Third-Party Recruiters

To protect you from recruitment scams, please be aware that Airwallex will not ask for bank details, sensitive ID numbers (i.e. passport), or any form of payment during the application or interview process. All official communication will come from an @airwallex.com email address. Please apply only through careers.airwallex.com or our official LinkedIn page.

Airwallex does not accept unsolicited resumes from search firms/recruiters. Airwallex will not pay any fees to search firms/recruiters if a candidate is submitted by a search firm/recruiter unless an agreement has been entered into with respect to specific open position(s). Search firms/recruiters submitting resumes to Airwallex on an unsolicited basis shall be deemed to accept this condition, regardless of any other provision to the contrary.

Equal opportunity

Airwallex is proud to be an equal opportunity employer. We value diversity and anyone seeking employment at Airwallex is considered based on merit, qualifications, competence and talent. We don’t regard color, religion, race, national origin, sexual orientation, ancestry, citizenship, sex, marital or family status, disability, gender, or any other legally protected status when making our hiring decisions. If you have a disability or special need that requires accommodation, please let us know.