Director of AI Analytics & CEO Office

We’re looking for a Director of AI Analytics & CEO Office to provide Airwallex’s Leadership with the data, tooling, and insights needed to amplify our rapid global growth. This team is the primary data advisor to the CEO and CFO, responsible for the models and insights that dictate where Airwallex places its biggest bets.

Responsibilities

Act as a strategic partner for the CEO, CFO, and Regional Business Leads, translating complex data landscapes into actionable business strategies; own Airwallex’s global forecasting engine and oversee development of sophisticated statistical models and tools that aggregate top-down and bottom-up forecasts to drive annual planning and capital allocation; lead development of causal inference frameworks to quantify the impact of macroeconomic shifts and internal interventions on global ecosystem; drive the roadmap for leveraging Generative AI and Machine Learning to automate insights, optimize business efficiency, and create proprietary data products; scale and lead a world-class team of data scientists and engineers, responsible for talent acquisition, performance management, and cultivating an environment of technical excellence and proactive critical thinking.

Requirements

10+ years in data science, analytics, or applied ML, including 5+ years leading teams at scale in top-tier tech, fintech, or growth-driven businesses; deep expertise in causal inference, time-series forecasting, and applied ML, with experience overseeing modern data stacks (Airflow, Databricks, dbt, Snowflake); expert-level proficiency in SQL and Python/R; Bachelor’s or Master’s degree in a quantitative field (e.g., Data Science, Computer Science, Statistics, Economics, Engineering) or equivalent practical experience; demonstrated experience working directly with executive leadership (C-suite/VP level) to influence corporate strategy using data; hands-on experience building and deploying advanced forecasting, causal inference, or machine learning models in a production environment; proficiency with modern data stack tools (SQL, Python, and cloud data warehouses like Snowflake or Databricks); proven track record of productionalizing Generative AI applications or agentic workflows to automate business intelligence and reporting.

Nice to have

Master or advanced degree in a highly quantitative discipline (e.g., Econometrics, Statistics, Machine Learning); experience working in Fintech, global payments, or high-growth B2B SaaS environments; experience operating within a CEO Office or corporate strategy function, balancing deep technical execution with high-level business acumen; familiarity with global macroeconomic indicators and their impact on cross-border transactional data.