Senior Data Scientist, GTM

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.

Our mandate is to use data-driven methods-not only to understand what changed, but to uncover why, and transform those insights into scalable impact.

As a Senior Data Scientist, GTM, you will play a pivotal role within the GTM Data Science team, partnering cross-functionally to develop innovative solutions to GTM challenges. Your work will encompass revenue forecasting, deep causal inference, and deploying AI-driven insights across the commercial lifecycle. You'll drive proactive, exploratory analysis, translate complex results into actionable business strategies, and help build Airwallex's next-generation data science foundation.

- Serve as a technical partner to Product, Growth, and Commercial teams to design and implement scalable data science solutions that accelerate revenue and improve commercial outcomes.

- Lead exploratory, data-driven analyses to identify and scale revenue opportunities, uncover trends, and operationalize insights into automated, repeatable workflows.

- Develop and maintain revenue forecasting models and performance analytics (e.g., pipeline health, conversion, retention drivers, scenario planning) as trusted sources of truth for commercial decision-making.

- Apply advanced causal inference techniques (such as DiD, synthetic control, DoubleML) to estimate business impact and guide strategic choices where RCTs are not practical.

- Design and implement AI-enabled solutions across the sales and customer lifecycle, including boosting sales effectiveness, retention, and expansion.

- Communicate technical findings and recommendations lucidly to technical and non-technical stakeholders, including executive teams.

We're looking for people who meet the minimum requirements for this role. The preferred qualifications are a plus, but not required.

- At least 5 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).

- Demonstrated analytical intuition and structured problem-solving; skilled at translating commercial questions into focused analytics projects.

- Excellent communicator, adept at presenting complex technical concepts as actionable recommendations to diverse audiences.

- Strong hands-on experience with SQL, Python and/or R, including causal inference and revenue forecasting.

- Deep curiosity about GTM performance and customer behavior-focused on uncovering not just what changed, but why it changed.

- Experience with Databricks or similar cloud data platforms/warehouses.

- Familiarity with Hex or other notebook-based analysis tools.

- Experience in a high-growth startup and/or B2B business models, including CRM, sales pipeline, or RevOps data.