Staff Data Scientist, Revenue

Airwallex2 months ago

Location

SG - Singapore

Type

Full Time

Level

Staff

Role

Data Scientist

Posted

Jan 15, 2026

Full TimeStaff

The role

Summary

A Staff Data Scientist role at Airwallex focused on revenue optimization and GTM analytics. The position involves building advanced forecasting models, applying causal inference methods, and embedding AI solutions into commercial workflows to drive revenue growth and improve sales effectiveness.

What you'll do

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

Model Development: Develop and own revenue forecasting and forward-looking performance insights including pipeline health, conversion and retention drivers, and scenario planning

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

AI Solution Design: Design and deploy AI-enabled solutions across the sales and customer lifecycle to enhance sales calls, coaching, and effectiveness

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

Data Science Operations: Operationalize learnings into repeatable workflows, automated pipelines, and scalable data science operating models

Customer Insights Generation: Generate proactive, transaction-based customer insights to drive retention and expansion strategies

What we look for

Technical

Advanced AnalyticsStrong foundations in causal inference and forecasting with experience in DiD, synthetic control, and modern ML-based approaches

Programming ProficiencyHigh fluency in SQL and proficiency in Python and/or R for analysis, modeling, and automation

Statistical ModelingDeep expertise in statistical methods and machine learning for business applications

Data Platform ExperienceExperience with cloud data platforms and warehouses, preferably Databricks

Education

Advanced DegreeMS or PhD in a quantitative field such as Statistics, Computer Science, Engineering, Economics, or related discipline

Experience

Industry Experience7+ years of industry experience in data science or related quantitative field

GTM AnalyticsDeep curiosity about GTM performance and customer behavior with focus on understanding root causes

Business ContextExperience in high-growth startup and/or B2B business models with pipeline, CRM, and RevOps data preferred

Communication SkillsExcellent communication and storytelling abilities to translate technical work into actionable recommendations

Skills

Required skills

Statistical AnalysisStrong analytical intuition and structured problem-solving with ability to ask the right questions and synthesize defensible conclusions

Causal InferenceDeep expertise in causal inference methods including DiD, synthetic control, and DoubleML for business impact estimation

Python/R ProgrammingProficiency in Python and/or R for advanced data analysis, modeling, and automation

SQL ExpertiseStrong SQL skills for data extraction, manipulation, and analysis

Business CommunicationAbility to translate technical work into clear, actionable recommendations for technical and non-technical stakeholders

Revenue AnalyticsUnderstanding of GTM performance metrics, customer behavior analysis, and revenue optimization strategies

Nice to have

DatabricksExperience with Databricks or similar cloud data platforms and warehouses

Hex PlatformFamiliarity with Hex or other notebook-based analysis tools for collaborative analytics

Startup ExperienceExperience in high-growth startup environments with fast-paced decision making

B2B AnalyticsExperience with B2B business models including pipeline analysis, CRM data, and RevOps metrics

AI/ML DeploymentExperience deploying AI-enabled solutions in production business environments

Compensation & benefits

Benefits

Global Impact

Work on complex, high-visibility problems with exceptional teammates in a global fintech leader

Career Growth

Accelerated learning opportunities and true ownership in building the future of global banking

Innovation Focus

Access to cutting-edge AI tools and technologies to solve problems faster and work smarter

Collaborative Environment

Work with over 2,000 of the brightest and most innovative people in tech across 26 global offices

Equal Opportunity

Commitment to diversity and equal opportunity employment based on merit, qualifications, and talent

Interview process

1
Application Review — Initial screening of resume and qualifications focusing on quantitative background and relevant experience
2
Technical Phone Screen — Phone interview covering statistical concepts, causal inference methods, and problem-solving approach
3
Case Study Interview — Hands-on analysis of a revenue analytics problem with presentation of findings and recommendations
4
Technical Deep Dive — In-depth technical interview covering advanced statistics, machine learning, and implementation experience
5
Stakeholder Communication — Interview focused on communication skills and ability to translate technical work for business audiences
6
Final Round — Meet with senior leadership and cross-functional partners to assess cultural fit and strategic thinking