Senior Data Scientist, Algorithm (Relo to SF)

Airwallex3 months ago

Location

AU - Sydney

Type

Full Time

Salary

USD 200,000 – 250,000

Level

Senior

Role

Data Scientist

Posted

Dec 4, 2025

Full TimeSenior

The role

Summary

This Senior Data Scientist role at Airwallex focuses on applying machine learning and statistical models to drive growth strategy across customer acquisition, retention, and personalization. The position requires 5+ years of industry experience with advanced ML modeling, production deployment experience, and strong stakeholder communication skills to influence marketing and commercial strategy decisions.

What you'll do

Predictive Model Development: 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, optimize referral incentive impacts and product cross-selling

Churn Modeling: Develop churn models to drive growth retention strategy

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

Strategic Communication: Communicate analysis results to executives and cross-functional teams to influence business strategy

Production Model Deployment: Build, deploy, and maintain machine learning models in production-grade systems

What we look for

Technical

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

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

Data Querying LanguagesExpert in SQL and other data querying languages

Programming LanguagesProficiency in scripting languages, particularly Python

Schema DesignExperience in schema design and dimensional data modeling

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 and analytics

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

High Growth EnvironmentExperience in technology, financial services, and/or high growth environment preferred

Skills

Required skills

Machine LearningExpert-level machine learning modeling for growth strategy

Statistical AnalysisAdvanced statistical modeling and causal inference techniques

PythonProficient in Python for data science and machine learning

SQLExpert-level SQL for data querying and analysis

Production MLExperience with production-grade ML system deployment

Executive CommunicationAbility to communicate complex analysis to executives and stakeholders

Nice to have

Financial ServicesExperience in fintech or financial services industry

High Growth EnvironmentExperience working in high-growth technology companies

Schema DesignExperience with dimensional data modeling and schema design

Cloud PlatformsExperience with cloud-based ML services and deployment

Real-time SystemsExperience with real-time and batch processing pipelines

Compensation & benefits

Salary

USD 200,000 – 250,000 (annual)

Benefits

Global Team Culture

Join a team of over 2,000 innovative people across 26 offices globally

High Impact Work

Work on complex, high-visibility problems with exceptional teammates

Career Growth

Accelerated learning opportunities and true ownership of projects

Equal Opportunity

Proud equal opportunity employer valuing diversity and inclusion

Accommodation Support

Accommodation provided for disabilities or special needs

Interview process

1
Application Review — Initial screening of resume and qualifications
2
Phone/Video Screen — Initial conversation with hiring team about background and interest
3
Technical Interview — Assessment of machine learning, statistical modeling, and data science skills
4
Case Study — Practical problem-solving exercise related to growth analytics and ML modeling
5
Stakeholder Interview — Discussion with cross-functional team members about collaboration and communication skills
6
Final Interview — Senior leadership interview focusing on strategic thinking and cultural fit