SlipstreamJobs tracks this role from the company's public career site. Apply directly on the employer's site.
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.
The Growth Data Science team sits at the center of Airwallex's growth engine, building advanced solutions—predictive modeling, personalization, LLM-powered systems, incentive optimization, and causal inference—to drive step-change growth across the customer lifecycle.
As Staff Data Scientist, you will partner closely with Growth and Marketing teams to design, deploy, and iterate on high-impact data science solutions that drive measurable business outcomes. Your work will directly shape Airwallex's growth strategy, influencing customer acquisition, engagement, and retention globally. 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.
Key responsibilities include:
- 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
You'll join during a critical period where Airwallex is building a team that enables both global consistency in process, tooling, and methodology while maintaining local flexibility and speed in execution.
REQUIREMENTS:
- 7+ years industry experience and an advanced degree (PhD or MS) in a quantitative field (e.g., Statistics, Engineering, Sciences, Computer Science, Economics)
- Experience communicating analysis results to leadership teams and cross-functional teams to influence strategy
- Technical mentorship experience with machine learning and experimentation in an industry setting
- Expert-level proficiency 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) and scripting languages (e.g., Python); experience in schema design and dimensional data modeling a plus
- Experience in technology, financial services, and/or high-growth environments is advantageous
