Senior Data Scientist, Algorithm - Growth

Airwallex8 months ago

Location

US - San Francisco

Type

Full Time

Salary

USD 200,000 – 250,000

Level

Senior

Role

Data Scientist

Posted

Jun 25, 2025

Full TimeSenior

The role

Summary

A Senior Data Scientist position at Airwallex focusing on growth algorithms to drive customer acquisition, engagement, and retention. The role involves building predictive models, applying machine learning for marketing impact measurement, and developing personalization solutions within a fast-growing fintech company valued at $8 billion.

What you'll do

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

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

Personalization Solutions: Develop personalization solutions to drive client onboarding efficiencies, optimize referral incentive impacts and product cross-selling

Churn Modeling: Develop churn models to drive growth retention strategy and customer lifecycle optimization

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

What we look for

Technical

Machine Learning ExpertiseExpert-level proficiency in machine learning modeling to drive data-driven growth strategy

Production ML SystemsHands-on experience building, deploying, and maintaining machine learning models in production-grade systems including cloud-based services and real-time/batch pipelines

Data Engineering SkillsExpert proficiency in SQL and Python, with experience in schema design and dimensional data modeling

Statistical AnalysisStrong foundation in statistical methods, causal inference, and experimental design for measuring marketing impact

Education

Advanced DegreePhD or MS in a quantitative field such as Statistics, Engineering, Sciences, Computer Science, or Economics

Experience

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

Executive CommunicationProven experience communicating analysis results to executives and cross-functional teams to influence strategic decisions

Fintech/High GrowthExperience in technology, financial services, or high-growth environment is advantageous

Skills

Required skills

Python ProgrammingAdvanced proficiency in Python for data science, machine learning, and automation workflows

SQL ExpertiseExpert-level SQL skills for complex data querying, extraction, and database operations

Machine LearningDeep expertise in ML algorithms, model development, evaluation, and production deployment

Statistical AnalysisStrong foundation in statistics, hypothesis testing, and causal inference methodologies

Business CommunicationAbility to translate complex technical insights into actionable business recommendations for executives

Nice to have

Fintech ExperienceBackground in financial technology or payments industry with understanding of regulatory requirements

Schema DesignExperience with dimensional data modeling and data warehouse architecture patterns

Growth MarketingUnderstanding of growth marketing strategies, customer lifecycle management, and retention analytics

MLOpsExperience with model deployment pipelines, monitoring, and production ML infrastructure

Compensation & benefits

Salary

USD 200,000 – 250,000 (annual)

Benefits

Global Team Culture

Join a diverse team of 2,000+ innovative professionals across 26 offices worldwide

High-Growth Environment

Work at a unicorn company valued at $8 billion with 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

Inclusive workplace committed to diversity and equal opportunity employment practices

Interview process

1
Initial Screen — Recruiter phone screen to assess basic qualifications and cultural fit with Airwallex values
2
Technical Assessment — Data science case study or coding challenge focusing on ML modeling and statistical analysis
3
Technical Interview — Deep dive into machine learning concepts, model deployment experience, and technical problem-solving
4
Business Case Discussion — Presentation of data science solution to a business problem, demonstrating communication and strategic thinking
5
Final Round — Panel interviews with team members and stakeholders to assess collaboration skills and growth mindset