Staff Data Scientist, GTM

About the role

The GTM Data Science team at Airwallex is a collaborative group of analytics and data science professionals passionate about driving commercial success with cutting-edge solutions. We work closely with Product, Growth, and Commercial teams to accelerate revenue growth, optimize efficiency, and build the data foundations supporting Airwallex's next phase.

Responsibilities

• Act as a technical partner to Product, Growth, and Commercial teams to design and implement data science solutions accelerating revenue and improving commercial outcomes.
• Lead exploratory analysis to identify and scale revenue levers, uncover emerging trends, and operationalize insights into robust, repeatable workflows.
• Develop and own revenue forecasting models and performance insights (e.g., pipeline health, conversion/retention drivers, scenario planning) that serve as a “source of truth” across the business.
• Apply advanced causal inference techniques (such as DiD, synthetic control, and DoubleML) to estimate impact and inform strategy when RCTs are infeasible.
• Design and deploy AI-enabled solutions throughout the sales and customer lifecycle, including sales effectiveness, retention, and expansion initiatives.
• Communicate technical results and recommendations clearly to both technical and non-technical stakeholders, including executives.
• Mentor and coach junior data scientists, providing technical guidance on high-impact, cross-functional projects.

Requirements

• At least 8 years of industry experience and an advanced degree (MS or PhD) in a quantitative field (e.g., Statistics, Computer Science, Engineering, Economics, or related discipline).
• Proven experience mentoring or leading data science or analytics teams.
• Strong analytical intuition and problem-solving skills; able to translate business questions into structured, high-impact analytic projects.
• Excellent communication skills; able to influence strategy and distill technical insights for varied audiences.
• Technical proficiency with SQL and Python and/or R; experience with causal inference and revenue forecasting is essential.
• Experience applying data science in technology, financial services, or high-growth settings.

Preferred Qualifications

• Experience with Databricks or similar cloud data platforms/warehouses.
• Familiarity with Hex or other notebook-based analysis tools.
• Background in B2B business models, CRM, pipeline, or RevOps data.
• Experience mentoring teams in fast-paced startup or fintech environments.