Senior Data Scientist, GTM
Data Scientist · Senior · Full Time
Opens Airwallex's application page
Role
What you'll do.
Airwallex is seeking a Senior Data Scientist to join their GTM team in San Francisco, focusing on revenue optimization and commercial efficiency through advanced analytics and AI solutions. This role combines deep statistical modeling with business impact, requiring expertise in causal inference, forecasting, and translating complex data insights into actionable business strategies for cross-functional teams.
Responsibilities
- Complex Analysis Translation: Transform complex statistical and modeling results into clear, actionable narratives for cross-functional partners and executive leadership
- Revenue Analytics Leadership: Lead proactive exploratory analyses to identify latent revenue levers, emerging trends, and root causes behind GTM metric shifts
- Scalable Model Development: Operationalize insights into repeatable workflows, automated pipelines, and scalable data science operating models
- Revenue Forecasting Ownership: Develop and maintain revenue forecasting and forward-looking performance insights including pipeline health and conversion drivers
- Advanced Causal Inference: Apply observational causal inference methods like DiD, synthetic control, and DoubleML to estimate impact when experiments aren't feasible
- AI Solution Implementation: Design and deploy AI-enabled solutions across sales and customer lifecycle to enhance effectiveness and generate proactive insights
- Cross-functional Partnership: Collaborate closely with Product, Growth, and Commercial teams to shape data science strategy and implementation
- Data Foundation Building: Build next-generation data science infrastructure and establish reliable 'source of truth' for commercial decision-making
Qualifications
What we look for.
Technical
Advanced SQL Proficiency
Strong SQL skills for complex data extraction and analytical query development
Python/R Expertise
High proficiency in Python and/or R for analysis, modeling, and automation workflows
Causal Inference Methods
Strong foundations in causal inference including DiD, synthetic control, and modern ML-based approaches
Forecasting and Time Series
Experience with revenue forecasting, time series analysis, and predictive modeling
Statistical Modeling
Advanced statistical analysis and machine learning model development and deployment
Analytics Tooling
Experience with cloud data platforms, notebook environments, and modern analytics stack
Education
Advanced Degree Required
MS or PhD in quantitative field such as Statistics, Computer Science, Engineering, Economics, or related discipline
Experience
Industry Experience
5+ years of industry experience in data science or quantitative analysis roles
GTM Analytics Experience
Experience with go-to-market performance analysis and customer behavior insights
Business Impact Focus
Proven track record of translating analytical work into measurable business outcomes
Executive Communication
Experience presenting technical findings to executive audiences and non-technical stakeholders
Skills
Required
Analytical Problem-Solving
Strong analytical intuition and structured approach to complex business problems
Technical Communication
Excellent ability to translate technical work into actionable recommendations for diverse audiences
Business Curiosity
Deep curiosity about GTM performance and customer behavior, going beyond descriptive to causal analysis
Statistical Foundations
Strong grounding in causal inference and forecasting methodologies
Programming Proficiency
High fluency in SQL, Python, and/or R for data analysis and modeling
Preferred
Databricks Experience
Nice to haveFamiliarity with Databricks or similar cloud data platforms and warehouses
Hex Platform Knowledge
Nice to haveExperience with Hex or other notebook-based analysis tools for collaborative analytics
Startup Experience
Nice to haveBackground in high-growth startup environments with fast-paced decision making
B2B Business Models
Nice to haveUnderstanding of B2B sales processes, pipeline management, CRM systems, and RevOps data
Financial Technology
Nice to haveExperience in fintech or payments industry with complex financial data analysis
Tech stack
Languages
Frameworks
Databases
Tools
Other
Compensation
Pay and benefits.
Base·USD 160,000 – 250,000
Equity·Stock options
Benefits
Equity Participation
Stock options in a rapidly growing fintech company valued at $8 billion
Global Career Opportunities
Access to 26 offices worldwide with international career development paths
Cutting-edge Technology
Work with state-of-the-art financial technology and data science infrastructure
High-Impact Projects
Opportunity to work on complex, high-visibility problems with exceptional teammates
Accelerated Learning
Fast-paced environment with significant professional growth opportunities
AI-Enhanced Productivity
Access to AI tools and resources to enhance work efficiency and problem-solving
Process
Interview steps.
- 01
Initial Screen
Phone or video call with recruiting team to discuss background and role fit
- 02
Technical Assessment
Take-home data science case study focusing on GTM analytics and causal inference
- 03
Technical Deep Dive
Technical interview covering statistical methods, causal inference, and past project experiences
- 04
Business Case Discussion
Present case study findings and discuss approach to solving GTM analytics challenges
- 05
Cross-functional Interview
Meet with Product, Growth, or Commercial team members to assess collaboration skills
- 06
Leadership Interview
Final interview with senior leadership focusing on strategic thinking and culture fit
Full posting
Original listing.
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 2,000 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.
Attributes We Value
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
We’re looking for talented candidates who can push the boundaries of our existing models and help design state-of-the-art solutions to GTM challenges that accelerate revenue growth and improve commercial efficiency. In this role, you’ll partner closely with Product, Growth, and Commercial teams to shape and build the next-generation data science foundation at Airwallex.
This role is ideal for someone who takes meaningful ownership from day one—someone who digs deeply into data to understand why outcomes change (not just what changed), balancing analytical rigor with speed and business context—and then leverages AI to translate those insights into scalable models and solid data foundations.
What you will do
Translate complexity into action: Turn complex statistical and modeling results into clear, compelling, and actionable narratives for cross-functional partners and executive audiences.
Uncover and scale revenue insights: Lead proactive, exploratory analyses to identify latent revenue levers, emerging trends, and root causes behind shifts in key GTM metrics—and operationalize these learnings into repeatable workflows, automated pipelines, and scalable data science operating models.
Build revenue forecasting and performance insights: Develop and own revenue forecasting and forward-looking performance insights (e.g., pipeline health, conversion and retention drivers, scenario planning), providing a reliable “source of truth” that helps teams make faster, better commercial decisions.
Apply advanced causal inference: Use advanced observational causal inference methods (e.g., DiD, synthetic control, DoubleML) to estimate impact and inform decisions when randomized experiments are infeasible.
Embed AI into commercial workflows: Design and deploy AI-enabled solutions across the sales and customer lifecycle—enhancing sales calls and coaching, improving sales effectiveness, and generating proactive, transaction-based customer insights to drive retention and expansion.
Who you are
5+ years of industry experience and an advanced degree (MS or PhD) in a quantitative field (e.g., Statistics, Computer Science, Engineering, Economics, or a related discipline).
Strong analytical intuition and structured problem-solving—you ask the right questions, explore data thoughtfully, and synthesize clear, defensible conclusions.
Excellent communicator and storyteller—able to translate technical work into crisp, actionable recommendations for both technical and non-technical stakeholders, including executives.
Deep curiosity about GTM performance and customer behavior—you go beyond “what happened” to understand “why it happened,” while staying pragmatic and focused on impact.
Strong foundations in causal inference and forecasting, with experience applying methods such as DiD, synthetic control, and modern ML-based approaches to real business problems.
High fluency in analytics tooling—strong SQL skills and proficiency in Python and/or R for analysis, modeling, and automation.
Nice to have
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 (e.g., pipeline, CRM, RevOps data).
Applicant Safety Policy: Fraud and Third-Party Recruiters
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.
Equal opportunity
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.
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