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We’re looking for talented Data Scientist 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.
Job Responsibility:
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
Requirements:
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
Excellent communicator and storyteller
Deep curiosity about GTM performance and customer behavior
Strong foundations in causal inference and forecasting
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)