Airwallex
Head of Growth Data Science
$300K–$320K
US - San Francisco · Hybrid · Director · Full-time · Posted Oct 7, 2026
- Experience
- 10+ years in data science, analytics, quantitative strategy, or applied machine learning; at least 5 years managing and developing high-performing technical teams.
- Education
- 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.
About the job
Leads Growth Data Science, using analytics, experimentation, and models to guide growth strategy and investment across customer lifecycle stages, markets, and products.
What you'll do
- Advise senior leaders and translate analysis into recommendations for growth strategy and investment decisions.
- Lead growth measurement, experimentation, causal inference, forecasting, and model development across the customer lifecycle.
- Set the roadmap for applying machine learning and Generative AI to growth analytics; build tools and partner with engineering to productionize models.
What they ask for
- Bachelor’s or Master’s degree in a quantitative field, or equivalent practical experience.
- 10+ years of experience in data science, analytics, quantitative strategy, or applied machine learning, including at least 5 years managing and developing technical teams.
- Hands-on production experience with experimentation, causal inference, forecasting, or machine learning; strong proficiency in SQL and Python or R.
- Experience partnering with senior leaders to influence growth strategy and productionizing Generative AI applications, intelligent analytics tools, or agentic workflows.
Nice to have
- Advanced degree in a quantitative discipline.
- Experience in fintech, payments, financial services, or high-growth B2B SaaS.
Pay
$300K – $320K USD base salary; offers equity and bonus (amounts not stated)
Tools
SQL, Python, R, Databricks, Snowflake, dbt, Airflow
AI focus
Define the roadmap for machine learning and Generative AI in growth analytics and decision-making, and build tools to automate insights, improve targeting, and increase operational efficiency.
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