Senior Data Scientist, GTM
Listed on 2026-06-27
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IT/Tech
Data Scientist, AI Engineer (Applied/Software), Data Analyst, Machine Learning/ ML Engineer
About Airwallex
Airwallex is the only unified payments and financial platform for global businesses. Powered by our unique combination of proprietary infrastructure and software, we empower over 200,000 businesses worldwide – including Brex, Rippling, Navan, Qantas, SHEIN and many more – with fully integrated solutions to manage everything from business accounts, payments, spend management and treasury, to embedded finance at a global scale.
Proudly founded in Melbourne, we have a team of over 2,200 of the brightest and most innovative people in tech across 26 offices around the globe. Valued at US $8 billion and backed by world-leading investors including T. Rowe Price, Visa, Mastercard, Robinhood Ventures, Sequoia, Salesforce Ventures, DST Global, and Lone Pine Capital, Airwallex is leading the charge in building the global payments and financial platform of the future.
If you’re ready to do the most ambitious work of your career, join us.
We hire successful builders with founder-like energy who want real impact, accelerated learning, and true ownership. You bring strong role-related expertise and sharp thinking, and you’re motivated by our mission and operating principles. You move fast with good judgment, dig deep with curiosity, and make decisions from first principles, balancing speed and rigor.
You're humble and collaborative; turn zero‑to‑one ideas into real products, and you “get stuff done” end-to-end. You use AI to work smarter and solve problems faster. Here, you’ll tackle complex, high‑visibility problems with exceptional teammates and grow your career as we build the future of global banking. If that sounds like you, let’s build what’s next.
About the team
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.
What you’ll do
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.
Responsibilities:
- 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.
Who you are
We’re looking for people who meet the minimum requirements for this role. The preferred qualifications are a plus, but not required.
Minimum qualifications:
- 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…
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