Senior Data Scientist, Revenue

Airwallex2 months ago

Location

SG - Singapore

Type

Full Time

Level

Senior

Role

Data Scientist

Posted

Jan 15, 2026

Full TimeSenior

The role

Summary

Airwallex is seeking a Senior Data Scientist to join their Revenue team in Singapore, focusing on building AI-powered solutions and advanced analytics to drive revenue growth and commercial efficiency. The role requires 5+ years of experience with an advanced degree in a quantitative field, strong expertise in causal inference, forecasting, and SQL/Python/R proficiency. The successful candidate will work closely with Product, Growth, and Commercial teams to develop revenue forecasting models, implement AI-enabled solutions across the sales lifecycle, and translate complex analytics into actionable business insights for executive stakeholders.

What you'll do

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

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

Scalable Model Development: 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 and retention drivers

Causal Inference Implementation: Apply 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 proactive customer insights

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

What we look for

Technical

Advanced Analytics SkillsStrong analytical intuition and structured problem-solving with ability to ask right questions and synthesize clear conclusions

Causal Inference 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

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

Education

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

Experience

Industry ExperienceMinimum 5+ years of industry experience in data science or related quantitative role

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

Cloud Platform ExperienceExperience with Databricks or similar cloud data platforms/warehouses preferred

Skills

Required skills

SQLStrong SQL skills for data querying and manipulation across cloud data platforms

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

Statistical AnalysisStrong foundations in causal inference, forecasting, and statistical modeling methods

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

Business AcumenDeep understanding of GTM performance, customer behavior, and commercial decision-making

Causal Inference MethodsExperience with DiD, synthetic control, DoubleML and other advanced observational methods

Nice to have

DatabricksExperience with Databricks or similar cloud data platforms and warehouses

HexFamiliarity with Hex or other notebook-based analysis tools for data science workflows

B2B ExperienceExperience in high-growth startup environment and B2B business models

CRM DataExperience working with pipeline, CRM, and RevOps data systems

AI/ML SolutionsExperience designing and deploying AI-enabled solutions in commercial workflows

Compensation & benefits

Benefits

Global Impact Opportunity

Work with over 200,000 businesses worldwide including Brex, Rippling, Navan, Qantas, SHEIN

Accelerated Career Growth

Real impact, accelerated learning, and true ownership in a fast-growing fintech unicorn valued at $8 billion

World-Class Team

Join 2,000+ brightest and most innovative people in tech across 26 global offices

Equal Opportunity Environment

Proud equal opportunity employer valuing diversity and considering candidates based on merit and qualifications

Accommodation Support

Accommodations provided for employees with disabilities or special needs

Interview process

1
Application Review — Initial screening of resume, portfolio, and application materials focusing on quantitative background and relevant experience
2
Phone/Video Screen — Initial conversation with hiring manager or recruiter to discuss background, motivation, and basic technical competencies
3
Technical Assessment — Data science case study or take-home assignment involving SQL, Python/R, statistical analysis, and business problem-solving
4
Technical Deep Dive — In-depth technical interview covering causal inference methods, forecasting approaches, and experience with relevant tools and platforms
5
Business Case Discussion — Interview focused on GTM analytics, revenue insights, and ability to translate complex findings into actionable business recommendations
6
Cross-functional Collaboration — Meet with potential stakeholders from Product, Growth, or Commercial teams to assess collaboration and communication skills
7
Final Interview — Senior leadership interview to assess cultural fit, leadership potential, and alignment with company values and mission