Head of Growth Data Science

US - San Francisco · 5+ years experience · Full-time · Hybrid · Posted Oct 7, 2026

At a glance

Airwallex is the AI-native financial operating system for a real-time, intelligent economy. More than 675,000 businesses, including McLaren Racing, Qantas, SHEIN, and TikTok, use us, directly or through our platform partners, to run their financial operations or build and monetize financial products of their own.
We started in Melbourne in 2015 to build the infrastructure global commerce runs on. We're the regulated backbone behind global payments: not by accident, but by design. A decade plus, 85+ licenses, and a financial infrastructure spanning North America, Europe, the Middle East, and Asia-Pacific.
We're co-headquartered in San Francisco and Singapore, with more than 2,300 people across 27 offices. We hire builders with founder-level energy, people who move fast with good judgment, dig in with real curiosity, and make calls from first principles rather than waiting to be told what to do. Read our operating principles https://www.airwallex.com/en-us/operating-principles to see it in full.

Airwallex is seeking a Head of Growth Data Science to lead the team responsible for using data, experimentation, and advanced analytics to accelerate global growth.
The Growth Data Science team partners closely with Product, Marketing, Sales, and regional business leaders to identify growth opportunities across the customer lifecycle.

Act as a strategic data partner to senior leaders across Growth, Product, Marketing, Sales, and regional businesses.
Translate complex analyses into clear recommendations that shape business strategy and investment decisions.
Establish a consistent, trusted framework for measuring growth performance across markets, channels, and customer segments.
Lead analytical efforts across the growth funnel, including acquisition, activation, conversion, retention, and expansion.
Identify opportunities to improve channel efficiency, customer journeys, pricing, and go-to-market performance.
Develop segmentation, propensity, attribution, and optimization models to inform growth initiatives.
Build and scale experimentation frameworks to measure the impact of product, marketing, and commercial initiatives.
Lead the application of causal inference techniques to distinguish correlation from true incremental impact.
Establish best practices for experiment design, measurement, interpretation, and decision-making.
Own forecasting and planning models that support growth targets, resource allocation, and business reviews.

Bachelor’s or Master’s degree in a quantitative field such as Data Science, Computer Science, Statistics, Economics, Mathematics, or Engineering, or equivalent practical experience.
10+ years of experience in data science, analytics, quantitative strategy, or applied machine learning.
At least 5 years of experience managing and developing high-performing technical teams.
Demonstrated experience partnering with executive and senior business leaders to influence growth strategy.
Hands-on experience with experimentation, causal inference, forecasting, or machine learning in a production environment.
Strong proficiency in SQL and Python or R.
Experience working with modern data platforms and tooling, such as Databricks, Snowflake, dbt, Airflow, or equivalent.
Proven ability to translate analytical insights into measurable business outcomes.
Experience productionizing Generative AI applications, intelligent analytics tools, or agentic workflows.

Advanced degree in Econometrics, Statistics, Machine Learning, Computer Science, Economics, or a related quantitative discipline.
Experience in fintech, payments, financial services, or high-growth B2B SaaS.
Experience leading data science teams across multiple growth functions, markets, or product lines.
Experience with customer lifecycle analytics, marketing measurement, attribution, pricing, or sales optimization.
Familiarity with global payments, cross-border commerce, and regional differences in customer and market behavior.
Experience building data products or decision systems used by senior executives and cross-functional teams.