Data Scientist, Algorithm (Growth)

Airwallex5 months ago

Location

US - San Francisco

Type

Full Time

Salary

USD 170,000 – 200,000

Level

Senior

Role

Data Scientist

Posted

Sep 30, 2025

Full TimeSenior

The role

Summary

Airwallex's Growth Data Science team is seeking a Senior Data Scientist to drive measurable business outcomes through advanced machine learning solutions, predictive modeling, and causal inference. The role focuses on customer acquisition, engagement, and retention optimization while working closely with Growth and Marketing teams at this $8B fintech unicorn.

What you'll do

Predictive Modeling: Develop predictive models to identify high-value users for Marketing and Commercial teams

Causal Impact Analysis: Apply machine learning and statistical models to measure causal impact of marketing initiatives

Personalization Solutions: Develop personalization solutions to drive client onboarding efficiencies and optimize referral incentive impacts

Cross-selling Optimization: Build models to optimize product cross-selling strategies and customer lifetime value

Churn Prevention: Develop churn models to drive growth retention strategy and reduce customer attrition

Cross-functional Collaboration: Partner with Marketing, Commercial, Engineering, and cross-functional teams to inform and execute GTM strategy

Strategic Decision Support: Provide data-driven insights to influence strategy and investment decisions across the organization

Model Deployment: Deploy and maintain machine learning models in production-grade systems with real-time capabilities

What we look for

Technical

Machine Learning ExpertiseExpert-level proficiency in machine learning modeling for data-driven growth strategies

Production ML SystemsHands-on experience building, deploying, and maintaining ML models in production-grade cloud systems

Programming LanguagesExpert proficiency in SQL for data querying and Python for scripting and model development

Data ArchitectureExperience in schema design and dimensional data modeling for analytics at scale

Statistical AnalysisAdvanced knowledge of statistical methods, causal inference, and experimental design

Education

Advanced DegreePhD or MS in quantitative field (Statistics, Engineering, Sciences, Computer Science, Economics)

Experience

Industry Experience5+ years of industry experience in data science or related quantitative roles

Executive CommunicationExperience communicating analysis results to executives and cross-functional teams to influence strategy

Growth EnvironmentExperience in technology, financial services, or high-growth environment preferred

Production SystemsProven track record of deploying ML models in production with batch and real-time pipelines

Skills

Required skills

PythonExpert-level proficiency for ML model development, data analysis, and automation

SQLAdvanced querying skills for complex data extraction and analysis

Machine LearningDeep expertise in supervised/unsupervised learning, model evaluation, and optimization

Statistical AnalysisAdvanced statistical methods, hypothesis testing, and causal inference techniques

Production MLExperience deploying and maintaining ML models in cloud-based production systems

Data ArchitectureSchema design, dimensional modeling, and data pipeline development

Executive CommunicationAbility to present complex findings to C-level executives and influence strategic decisions

Nice to have

Fintech ExperienceBackground in financial services, payments, or fintech industry

Growth AnalyticsExperience with user acquisition, retention, and lifecycle optimization models

A/B TestingExpertise in experimental design, causal inference, and marketing measurement

Real-time SystemsExperience with streaming data and real-time model serving architectures

LLM IntegrationKnowledge of large language models and their application in business contexts

MLOpsExperience with ML operations, model monitoring, and automated deployment pipelines

Compensation & benefits

Salary

USD 170,000 – 200,000 (annual)

Benefits

Global Impact

Work on solutions affecting 200,000+ businesses worldwide including major brands like Brex, Rippling, and SHEIN

Career Growth

Accelerated learning opportunities in a fast-growing $8B fintech unicorn

Innovation Focus

Access to cutting-edge AI and ML technologies with real business impact

Global Team

Collaborate with 2,000+ top-tier professionals across 26 offices worldwide

Equity Opportunity

Potential equity participation in a rapidly scaling fintech company

Flexible Work

Hybrid work arrangement with office presence in San Francisco

Interview process

1
Application Review — Initial screening of resume, portfolio, and technical background by recruiting team
2
Recruiter Phone Screen — 30-minute call to discuss background, motivation, and role expectations
3
Hiring Manager Interview — 45-minute discussion about experience, approach to data science problems, and team fit
4
Technical Case Study — Take-home assignment or live coding session focusing on ML modeling and business problem-solving
5
Technical Deep Dive — 60-minute interview covering ML concepts, statistical methods, and production system design
6
Cross-functional Panel — Panel interview with Growth, Marketing, and Engineering stakeholders to assess collaboration skills
7
Final Round — Leadership interview focusing on strategic thinking, communication skills, and cultural alignment
8
Reference Check — Verification of past performance and team collaboration with previous managers or colleagues