Senior Data Scientist, GTM Analytics

Airwallex3 months ago

Location

SG - Singapore

Type

Full Time

Level

Senior

Role

Data Scientist

Posted

Dec 7, 2025

Full TimeSenior

The role

Summary

Airwallex is seeking a Senior Data Scientist for GTM Analytics to build state-of-the-art solutions that accelerate revenue growth and improve commercial efficiency. The role involves partnering with Product, Growth, and Commercial teams to develop revenue forecasting models, apply causal inference methods, and embed AI into commercial workflows. This position requires 5+ years of experience with an advanced degree in a quantitative field, strong expertise in SQL, Python/R, and causal inference methods.

What you'll do

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

Forecasting and performance modeling: 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 deployment: Design and deploy AI-enabled solutions across the sales and customer lifecycle to enhance sales effectiveness and generate customer insights

Cross-functional communication: Translate complex statistical and modeling results into clear, compelling, and actionable narratives for executives and cross-functional partners

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

What we look for

Technical

Statistical modeling expertiseStrong 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

Data analysis skillsStrong analytical intuition and structured problem-solving with ability to explore data thoughtfully

Education

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

Experience

Industry experience5+ years of industry experience in data science or related analytical roles

GTM analytics experienceDeep curiosity about GTM performance and customer behavior with focus on business impact

Communication skillsExcellent communicator and storyteller able to translate technical work for both technical and non-technical stakeholders

Skills

Required skills

SQLStrong SQL skills for data querying and database operations

Python/RProficiency in Python and/or R for analysis, modeling, and automation

Causal inferenceExperience with DiD, synthetic control, DoubleML and other causal inference methods

Statistical modelingStrong foundations in forecasting and statistical analysis

CommunicationAbility to translate technical work into actionable recommendations for stakeholders

Nice to have

DatabricksExperience with Databricks or similar cloud data platforms and warehouses

HexFamiliarity with Hex or other notebook-based analysis tools

Startup experienceExperience in high-growth startup environment

B2B analyticsExperience with B2B business models including pipeline, CRM, and RevOps data

Compensation & benefits

Benefits

Global company exposure

Work with a team of over 2,000 innovative professionals across 26 offices globally

High-growth environment

Join a $8 billion valuation company backed by world-leading investors including T. Rowe Price, Visa, and Mastercard

Career development

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

Equal opportunity workplace

Proud equal opportunity employer that values diversity and inclusion

Interview process

1
Initial screening — Phone or video call to discuss background and interest in the role
2
Technical assessment — Evaluation of statistical modeling, causal inference, and programming skills
3
Case study presentation — Present analysis of a business problem demonstrating GTM analytics expertise
4
Cross-functional interviews — Meet with potential stakeholders from Product, Growth, and Commercial teams
5
Final interview — Discussion with senior leadership focusing on strategic thinking and cultural fit