About Airwallex

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 2,700 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 to see it in full.

How you'll make impact

Growth is becoming a more measurable, intelligent system across product, sales, and marketing. You'll lead the data science team that turns customer and business signals into better growth decisions and measurable outcomes.

Lead the team responsible for using data, experimentation, and advanced analytics to accelerate Airwallex's global growth.

Partner with Product, Marketing, Sales, and regional business leaders to identify opportunities across acquisition, activation, conversion, retention, and expansion.

Define a consistent measurement framework across markets, channels, and customer segments, and turn complex analysis into clear recommendations that shape strategy and investment decisions.

Set the roadmap for machine learning, generative AI, experimentation, causal inference, forecasting, and intelligent decision systems across growth.

Build and scale analytical products, models, and tools that improve targeting, automate insight generation, connect operating drivers with financial outcomes, and guide next-best actions.

Partner with engineering and data platform teams to productionize models and analytical products, while building a high-performing, technically rigorous team.

You'll work from our San Francisco office three days a week.

What we're looking for

Essentials

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.

A 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.

Deep expertise in experimentation, causal inference, forecasting, applied machine learning, SQL, and Python or R.

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.

A proven ability to translate analytical insights into measurable business outcomes.

Experience productionizing generative AI applications, intelligent analytics tools, or agentic workflows.

The ability to prioritize ambiguous problems, balance trade-offs, and focus teams on initiatives with measurable growth impact.

The ability to engage deeply with technical work while building scalable systems, analytical frameworks, and team practices.

Clear communication skills, with the ability to influence senior stakeholders through rigorous analysis and practical recommendations.

A customer-centric approach to understanding behavior and using data to create better experiences and stronger business outcomes.

Preferred

An 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.