Senior Data Scientist, Algorithm (Lending & Onboarding)

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 2,300 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 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 GTPN, Payments, Issuing, Onboarding, Account Takeover, Lending, and Credit. 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 Senior Data Scientist, you will tackle challenging risk problems across credit and fraud (e.g., account takeover), and help build data-driven decision systems that deliver meaningful business impact. You will be responsible for translating business problems into analytical frameworks, strategies, models, and scalable data solutions.

Responsibilities:

• Build real-time ML models to protect Airwallex customers and platform assets, such as Account Takeover prevention and fraud decisioning

• Develop credit risk models and analytical frameworks to assess merchant risk and support the growth of Airwallex’s lending business

• Translate business requirements into analytical, modeling, and strategy problems across fraud, credit, onboarding, and related risk domains

• Design performance monitoring, metrics frameworks, and decision-support tools to improve risk visibility and decision quality

• Partner with Product, Engineering, Operations, and other cross-functional teams to turn data, models, and insights into production strategies and measurable business impact

Who You Are

We're looking for people who meet the minimum qualifications for this role. The preferred qualifications are great to have, but are not mandatory.

Minimum qualifications:

• 3+ years of experience in analytics, data science, risk strategy, or a related quantitative role

• Bachelor’s degree or above in a quantitative field such as Statistics, Mathematics, Economics, Computer Science, Engineering, or a related discipline

• Proficient in Python and SQL

• Strong problem-solving skills and experience working with large datasets

• Experience partnering with cross-functional stakeholders to solve business problems

Preferred qualifications:

• Experience in credit, fraud, or related risk domains

• Hands-on experience in model development, validation, or monitoring

• Experience designing risk rules, decision strategies, or performance monitoring frameworks

Why Join Us:

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