Staff Data Scientist, GTM Analytics

Airwallex3 days ago

Location

SG - Singapore

Type

Full Time

Level

Staff

Role

Data Scientist

Posted

Mar 11, 2026

Full TimeStaff

The role

Summary

This Staff Data Scientist role at Airwallex focuses on GTM Analytics, working with Product, Growth, and Commercial teams to build revenue forecasting models and AI-enabled solutions. The position requires 7+ years of experience with advanced degree in quantitative fields, strong SQL/Python skills, and expertise in causal inference methods like DiD and synthetic control.

What you'll do

Complex Analysis Translation: Translate complex statistical and modeling results into clear, compelling, and actionable narratives for cross-functional partners and executive audiences

Revenue Insights Leadership: Lead proactive, exploratory analyses to identify latent revenue levers, emerging trends, and root causes behind shifts in key GTM metrics

Model Operationalization: Operationalize insights into repeatable workflows, automated pipelines, and scalable data science operating models

Revenue Forecasting: Develop and own revenue forecasting and forward-looking performance insights including pipeline health, conversion drivers, and scenario planning

Causal Inference Application: Use advanced observational causal inference methods (DiD, synthetic control, DoubleML) to estimate impact when randomized experiments are infeasible

AI Solution Development: Design and deploy AI-enabled solutions across sales and customer lifecycle to enhance effectiveness and drive retention

Cross-functional Collaboration: Partner closely with Product, Growth, and Commercial teams to shape next-generation data science foundation

Data-Driven Decision Support: Provide reliable 'source of truth' analytics that help teams make faster, better commercial decisions

What we look for

Technical

SQL ProficiencyHigh fluency in SQL for complex data querying and manipulation across enterprise data platforms

Python/R ProgrammingStrong proficiency in Python and/or R for statistical analysis, modeling, and automation workflows

Causal Inference MethodsDeep expertise in causal inference techniques including Difference-in-Differences, synthetic control, and DoubleML frameworks

Forecasting TechniquesStrong foundation in time series forecasting and predictive modeling methodologies

Machine LearningExperience with modern ML approaches for business problem solving and model deployment

Education

Advanced Degree RequiredMaster's or PhD in quantitative field such as Statistics, Computer Science, Engineering, Economics, or related discipline

Experience

Industry ExperienceMinimum 7+ years of industry experience in data science or analytics roles

GTM Analytics BackgroundExperience working with go-to-market data, sales performance metrics, and commercial analytics

Cross-functional CollaborationProven track record of partnering with Product, Growth, and Commercial teams

Executive CommunicationExperience presenting technical findings to executive audiences and non-technical stakeholders

Skills

Required skills

Statistical AnalysisStrong analytical intuition and structured problem-solving approach to complex business problems

Technical CommunicationExcellent storytelling ability to translate technical work into actionable recommendations

Business AcumenDeep curiosity about GTM performance and customer behavior with pragmatic focus on impact

Causal InferenceExpertise in DiD, synthetic control, and modern ML-based causal methods

Data EngineeringAbility to build automated pipelines and scalable data science workflows

Nice to have

Cloud PlatformsExperience with Databricks or similar cloud data warehouse platforms

Notebook ToolsFamiliarity with Hex or other collaborative notebook-based analysis environments

Startup ExperienceBackground in high-growth startup environments with B2B business models

RevOps KnowledgeUnderstanding of pipeline, CRM, and revenue operations data systems

Compensation & benefits

Benefits

Global Opportunities

Work with international teams across 26 offices globally

High-Growth Environment

Join a fast-growing fintech unicorn valued at $8 billion

Learning & Development

Accelerated learning opportunities in cutting-edge financial technology

Equity Participation

Opportunity to own equity in a rapidly scaling global fintech company

Innovation Focus

Work on state-of-the-art AI and machine learning solutions

Career Growth

Build career in next-generation global banking and payments infrastructure

Interview process

1
Initial Screen — Phone or video interview with hiring manager to discuss background and role fit
2
Technical Assessment — Take-home case study involving GTM analytics, causal inference, and business problem solving
3
Technical Deep Dive — Technical interview focusing on statistical methods, SQL, Python/R programming, and causal inference
4
Business Case Presentation — Present case study solution to cross-functional team including Product and Commercial stakeholders
5
Leadership Interview — Interview with senior data science leadership and executives focusing on strategic thinking
6
Culture Fit — Final round with team members to assess collaboration style and cultural alignment