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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 provides regulated financial infrastructure spanning North America, Europe, the Middle East, and Asia-Pacific, with 2,300+ employees across 27 offices.
As a Staff Data Scientist, you will drive strategic impact through rigorous analysis, forecasting, and data storytelling while combining hands-on technical leadership with organization-wide influence. Your responsibilities include:
- Upleveling the data science team through technical mentorship, hands-on leadership on complex analytical problems, and establishing a clear vision for the team's longer-term direction.
- Serving as a strategic thought partner to cross-functional teams, using data and technical expertise to inform, influence, and execute strategy and investment decisions.
- Applying quantitative analysis, data mining, forecasting, and clear data storytelling to answer critical business questions and guide strategic decisions.
- Defining goals, building forecasts, and monitoring key business metrics to identify trends and assess performance across the organization.
- Evolving data science from individual analyses into scalable systems of decision support, establishing robust analytical approaches that produce reliable insights repeatedly.
The data science function at Airwallex is transitioning from standalone analyses and models into scalable systems of decision and action. You'll build systems that help teams understand what changed, determine next steps, and validate outcomes. This includes owning the AI analytics infrastructure—semantic layers, context retrieval, evaluation infrastructure, validation gates, and governance—to ensure decisions remain reliable and trustworthy at scale. You'll also design systems that use machine learning and AI to optimize product behavior, ranking, pricing, risk, allocation, and customer experiences.
As AI makes ad hoc analysis increasingly accessible, the competitive advantage lies in scale, scientific method, and rigor. You'll structure ambiguous problems, design experiments, identify confounding factors, challenge misleading conclusions, and build production systems that reliably produce outcomes repeatedly. The work is moving up the stack: from analysis to system, from model to harness, and from answering a question once to building something that answers it correctly over time.
You'll work from the London office three days per week.
REQUIREMENTS:
- 8+ years of industry experience in data science or quantitative analysis.
- Advanced degree (PhD or MS) in a quantitative field such as Statistics, Engineering, Sciences, Computer Science, or Economics.
- Demonstrated experience communicating analytical results to leadership and cross-functional teams to influence strategy.
- Proven experience providing technical mentorship in data science or quantitative analysis in an industry setting.
- Expert-level proficiency in data-querying languages (SQL), scripting languages (Python), and/or statistical/mathematical software (R).
- Comfort owning roadmaps independently and taking ownership of outcomes without waiting for permission.
- Ability to work comfortably with ambiguity and run with problems rather than prescriptions.
- Strong ability to connect dots across functions while maintaining both big-picture and detail-oriented perspectives.
- Skill in simplifying complexity rather than hiding behind it.
