Staff Data Scientist, GTM

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 250,000 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 2,300 of the brightest and most innovative people in tech across 27 offices around the globe. Valued at US$11 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 Staff Data Scientist, GTM, you will be a technical leader within the GTM Data Science team, partnering cross-functionally to develop state-of-the-art solutions to GTM challenges. Your work will span revenue forecasting, causal inference, and embedding AI-driven insights across the commercial lifecycle. You’ll drive proactive, exploratory analysis, translate complex modeling into clear business actions, and help shape the data science operating model at Airwallex.

This hybrid role is based in San Francisco or New York City.

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.

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 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.

To protect you from recruitment scams, please be aware that Airwallex will not ask for bank details, sensitive ID numbers (i.e. passport), or any form of payment during the application or interview process. All official communication will come from an @airwallex.com email address. Please apply only through careers.airwallex.com or our official LinkedIn page.

Airwallex does not accept unsolicited resumes from search firms/recruiters. Airwallex will not pay any fees to search firms/recruiters if a candidate is submitted by a search firm/recruiter unless an agreement has been entered into with respect to specific open position(s). Search firms/recruiters submitting resumes to Airwallex on an unsolicited basis shall be deemed to accept this condition, regardless of any other provision to the contrary.

Airwallex is proud to be an equal opportunity employer. We value diversity and anyone seeking employment at Airwallex is considered based on merit, qualifications, competence and talent. We don’t regard color, religion, race, national origin, sexual orientation, ancestry, citizenship, sex, marital or family status, disability, gender, or any other legally protected status when making our hiring decisions. If you have a disability or special need that requires accommodation, please let us know.