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Airwallex is a unified payments and financial platform serving over 250,000 global businesses including Brex, Rippling, Navan, and Qantas. The company operates across 27 offices worldwide with 2,300+ employees and is valued at $11 billion, backed by leading investors including Sequoia, Visa, and Mastercard.
The Risk Platform team manages risk across all Airwallex products—lending, payments, issuing, and onboarding—operating at the forefront of innovation in risk management.
As a Senior Data Scientist in Credit Risk Analytics for Lending, you will monitor and optimize the performance of Airwallex's business lending portfolio through data-driven analysis and actionable recommendations. You'll translate complex portfolio and policy questions into analytical frameworks and monitoring approaches that improve credit quality and support sustainable growth.
Key responsibilities include: monitoring and analyzing business lending portfolio performance (delinquency trends, early warning indicators, credit quality metrics); identifying emerging risks and providing mitigation insights; supporting assessment and optimization of portfolio-level credit strategies aligned with regional policies; preparing portfolio reports, risk dashboards, and management summaries for senior leadership; collaborating with Operations and Product teams on credit policy application and risk controls; participating in portfolio reviews, stress testing, and credit risk assessments; and providing analytical support for regulatory reporting and governance.
You bring 3+ years of credit risk analytics, risk strategy, portfolio analytics, or related quantitative experience. You hold a bachelor's degree or above in Quantitative Finance, Statistics, Computer Science, Business Analytics, Data Science, or related discipline. You're proficient in SQL and Python with demonstrated ability to translate data into actionable insights. You have strong problem-solving skills, attention to detail, and experience partnering with cross-functional stakeholders.
Preferred qualifications include hybrid risk analytics and modeling experience, SME lending background, hands-on ECL modeling or credit strategy analysis, experience designing credit policies or performance monitoring frameworks, and familiarity with stress testing, governance, audit, or regulatory reporting.
