Data Scientist (Mid and Senior Level)

**Our Story** **Hello there. We’re Zopa.** We started our journey back in 2005, building the first ever peer-to-peer lending company. Fast forward to 2020 and we launched Zopa Bank. A bank that listens to what our customers don’t like about finance and does the opposite. We’re redefining what it feels like to work in finance. Our vision for a new era of banking puts people front and centre — we’ve built a business that empowers everyone to aim high, every day, to move finance forward. Find out more about our fantastic offerings at [](http://Zopa.com)! We’re incredibly proud of our achievements and none of it would be possible without the amazing team here. It’s not just industry awards we’re winning, we’ve also been named in the top three UK’s Most Loved Workplaces. If you embrace unconventional challenges, are unafraid to think differently and are driven to make an outsized impact, you’ll thrive here at Zopa, so join us, and make it count. Want to see us in action? Follow us on Instagram @zopalife **The team** Our Data Science team helps Zopa make better credit decisions. We partner closely with Credit Strategy, Product and Engineering to turn ambiguous business problems into robust models, clear analysis and practical solutions. We are growing a dedicated, product-facing data science capability focused predominantly on credit. The team will help rebuild and expand the models that support consumer-credit decisions, while increasing the sophistication of how we model risk, value and outcomes. This is a hands-on individual-contributor role in a lean, collaborative environment. You will have real ownership, with space to shape the work and build alignment across the people needed to make it happen. We are hiring at both mid and senior level, and will assess candidates at the level that best reflects their experience, technical depth and scope of impact. ### A day in the life - Take ambiguous credit-related questions from stakeholder discussion through to practical modelling 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 judgement 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 productionisation - 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 that works together ### About you - You have hands-on data science experience - Bring practical Python and Git capability - Understand common statistical-learning models and machine-learning algorithms for classification and regression - Have sound statistical fundamentals, including hypothesis testing and experimental design - Can independently take an ambiguous problem from discussion to a useful model or analysis - Communicate clearly and confidently with technical and non-technical stakeholders - Build alignment when there are differing views, and enjoy working collaboratively to move things forward - Are curious, practical and comfortable operating with limited hand-holding - Work effectively across business, Product and Engineering partners **Added bonus** - Experience in consumer credit, lending, credit cards or a closely related credit-risk domain - Exposure to sequence-based deep-learning or transformer-style models - Experience building production-grade Python microservices