Airwallex
Senior Data Scientist, Analytics (Lending)
- Employment type
- Full-time
- Workplace type
- On-site
- Location
- SG - Singapore
- Published
- Jul 28, 2026
- Last checked
- Oct 26, 2026
About this role
ABOUT AIRWALLEX
Airwallex is the AI-native financial operating system for a real-time, intelligent economy. More than 675,000 businesses, including McLaren Racing, Qantas, SHEIN, and TikTok, use us, directly or through our platform partners, to run their financial operations or build and monetize financial products of their own.
We started in Melbourne in 2015 to build the infrastructure global commerce runs on. We're the regulated backbone behind global payments: not by accident, but by design. A decade plus, 85+ licenses, and a financial infrastructure spanning North America, Europe, the Middle East, and Asia-Pacific.
We're co-headquartered in San Francisco and Singapore, with more than 2,700 people across 27 offices. We hire builders with founder-level energy, people who move fast with good judgment, dig in with real curiosity, and make calls from first principles rather than waiting to be told what to do. Read our operating principles https://www.airwallex.com/en-us/operating-principles to see it in full.
ABOUT THE TEAM
The risk platform team at Airwallex is responsible for managing risk across all Airwallex products, including topics like lending, Payments, Issuing and Onboarding. The risk landscape is constantly changing, and threats are becoming increasingly sophisticated. We are at the forefront of innovation in risk management.
WHAT YOU’LL DO
As a Credit Risk Analyst - Lending, you will help monitor and optimize the performance of Airwallex’s business lending portfolio through data-driven analysis, portfolio insights, and credit risk strategy support. You will be responsible for translating portfolio and policy questions into analytical frameworks, monitoring approaches, and actionable recommendations that improve credit quality and support sustainable business growth.
RESPONSIBILITIES:
- Monitor and analyze the performance of existing business lending portfolios, including delinquency trends, early warning indicators, and credit quality metrics