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Zopa is a fintech company founded in 2005 as the first peer-to-peer lending platform, and launched Zopa Bank in 2020 to redefine consumer banking. The Data Science team partners with Credit Strategy, Product, and Engineering to turn business problems into robust models and practical solutions.
In this hands-on individual-contributor role, you will have real ownership and space to shape work while building alignment across stakeholders. You'll work on a lean, collaborative team focused on consumer-credit decisions and risk modeling.
Key responsibilities:
- Take ambiguous credit-related questions from stakeholder discussion through to practical modeling and analysis
- Build, improve, and maintain models that support consumer-credit decisions
- Work on flagship risk models and broader value-driver models, including revenue, profit prediction, and customer lifetime value
- Use Python and sound statistical judgment to develop classification and regression solutions
- Partner with Credit Strategy to understand priorities and create useful, well-framed solutions
- Collaborate with Product and Engineering to sequence work and support productionization
- Explain technical choices clearly, build consensus where views differ, and help move decisions forward
- Own your problems and delivery while contributing to a low-ego team
The role is hybrid, requiring 2-3 days per week in the London office, with the option to work from abroad for up to 120 days per year (subject to work authorization).
Requirements:
- Hands-on data science experience
- Practical Python and Git capability
- Understanding of common statistical-learning models and machine-learning algorithms for classification and regression
- Sound statistical fundamentals, including hypothesis testing and experimental design
- Ability to independently take an ambiguous problem from discussion to a useful model or analysis
- Clear communication with technical and non-technical stakeholders
- Ability to build alignment when views differ and work collaboratively
- Curious, practical mindset and comfort operating with limited hand-holding
- Effective cross-functional collaboration with business, Product, and Engineering partners
Bonus qualifications:
- Experience in consumer credit, lending, credit cards, or closely related credit-risk domain
- Exposure to sequence-based deep-learning or transformer-style models
- Experience building production-grade Python microservices
