Senior Data Scientist, Analytics (Lending)
Airwallex
- Location
- SG - Singapore
- Employment
- Full Time
- Work model
- On-Site
- Level
- Senior
- Posted
- 15h ago
Skills
About this role
About Airwallex Airwallex is the only unified payments and financial platform for global businesses. Powered by our unique combination of proprietary infrastructure and software, we empower over 250,000 businesses worldwide – including Brex, Rippling, Navan, Qantas, SHEIN and many more – with fully integrated solutions to manage everything from business accounts, payments, spend management and treasury, to embedded finance at a global scale. Proudly founded in Melbourne, we have a team of over 2,300 of the brightest and most innovative people in tech across 27 offices around the globe. Valued at US$11 billion and backed by world-leading investors including T. Rowe Price, Visa, Mastercard, Robinhood Ventures, Sequoia, Salesforce Ventures, DST Global, and Lone Pine Capital, Airwallex is leading the charge in building the global payments and financial platform of the future. If you’re ready to do the most ambitious work of your career, join us. Attributes We Value We hire successful builders with founder-like energy who want real impact, accelerated learning, and true ownership. You bring strong role-related expertise and sharp thinking, and you’re motivated by our mission and operating principles . You move fast with good judgment, dig deep with curiosity, and make decisions from first principles, balancing speed and rigor. You're humble and collaborative; turn zero‑to‑one ideas into real products, and you “get stuff done” end-to-end. You use AI to work smarter and solve problems faster. Here, you’ll tackle complex, high‑visibility problems with exceptional teammates and grow your career as we build the future of global banking. If that sounds like you, let’s build what’s next.
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 Identify emerging risks within the portfolio and provide actionable insights to mitigate potential losses Support the assessment and optimization of portfolio-level credit strategies, ensuring alignment with regional credit risk policies Prepare portfolio reports, risk dashboards, and management summaries to support senior leadership decision-making Collaborate with Operations and Product teams to ensure consistent application of credit policies and effective risk controls Participate in periodic portfolio reviews, stress testing, and credit risk assessment exercises Provide analytical support for regulatory reporting, audits, and internal governance requirements 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 credit risk analytics, risk strategy, portfolio analytics, or a related quantitative role Bachelor’s degree or above in Quantitative Finance, Statistics, Computer Science, Business Analytics, Data Science, or a related quantitative discipline Proficient in SQL and Python, with the ability to translate data into actionable insights Strong problem-solving skills and experience working with large datasets Strong