Staff Data Scientist, GTM

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.

Applicant Safety Policy: Fraud and Third-Party RecruitersTo 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.

Equal opportunityAirwallex 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.