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Airwallex is an AI-native financial operating system serving over 675,000 businesses globally, including McLaren Racing, Qantas, SHEIN, and TikTok. The company operates as a regulated backbone for global payments across North America, Europe, the Middle East, and Asia-Pacific, with 2,300+ employees across 27 offices.
In this Staff Data Scientist role, you will shape the next phase of Airwallex's growth by building data science systems that improve customer acquisition, activation, engagement, retention, and expansion globally. You'll design, deploy, and iterate on predictive models, personalization and recommendation systems, LLM-powered applications, incentive optimization frameworks, and causal inference models that drive measurable business outcomes.
Key responsibilities include:
- Designing and deploying machine learning systems that directly optimize product behavior, ranking, pricing, risk, allocation, and customer experiences
- Partnering with Growth, Marketing, Product, Sales, Engineering, and cross-functional teams to translate data and AI into clear recommendations and effective go-to-market strategies
- Measuring causal impact of marketing and growth initiatives, identifying what works, and translating findings into action
- Raising the technical bar for the data science team through hands-on leadership, mentorship, and vision-setting for longer-term direction
- Building systems of decision and action that help teams understand what changed, determine next steps, and learn whether actions worked
- Owning the AI analytics harness including semantic layers, context retrieval, evaluation infrastructure, validation gates, and governance
You'll be based in Seattle and work from the office three days per week. The role focuses on moving data science up the stack—from ad hoc analysis to scalable systems, from individual models to production harnesses, and from one-off answers to reliable, repeatable outcomes. You'll structure ambiguous problems, design experiments, identify confounding factors, and build production systems that produce reliable outcomes at scale.
REQUIREMENTS:
- 7+ years of industry experience and an advanced degree (PhD or MS) in a quantitative field such as Statistics, Engineering, Sciences, Computer Science, or Economics
- Expert knowledge of machine learning and statistical modeling for data-driven growth strategy
- Hands-on experience building, deploying, and maintaining machine learning models in production-grade systems, including cloud-based services and real-time or batch pipelines
- Strong experience with SQL and Python
- Experience applying machine learning and statistical models to measure causal impact of marketing or growth initiatives
- Strong experience in AI harness and building AI agents
PREFERRED:
- Experience with schema design and dimensional data modeling
- Experience communicating analysis and recommendations to leadership and cross-functional teams to influence strategy
- Background in technology, financial services, or high-growth environments
- Experience providing technical mentorship on machine learning and experimentation in industry settings
