A day in the life...
- Explore the current enrichment pipeline to understand how it works and where it fails
- Form hypotheses about where accuracy is breaking down (e.g. merchant ambiguity, edge cases, new patterns)
- Write code (typically SQL and/or Python) to analyse performance, quantify what's working, and identify systematic gaps
- Build quick prototypes or enrichment experiments to test alternative approaches
- Run structured evaluations, interpret results carefully, and communicate trade-offs clearly
- Work closely with Product and Engineering to embed improvements into long-term system design
- Use AI and LLM tools pragmatically - for exploration, pattern detection, prototyping logic and accelerating experimentation
- Continuously look for deeper patterns and structural improvements rather than settling for surface-level fixes
About you...
- You're naturally curious. When you see messy or imperfect data, you want to understand why. You’re also curious about modern AI and LLM tools and have experimented with using building things with them, at work or as personal projects
- Comfortable being given a broad problem and figuring out how to structure it
- You enjoy forming hypotheses, writing code to test them, and interrogating results deeply
- Strong SQL skills and ideally experience using Python for exploratory analysis or prototyping
- You’ve worked in a data-led, fast-paced environment (e.g. fintech, banking, start-up, consulting)
- Ability to communicate clearly and can explain complex findings to both technical and non-technical audiences
- You’re collaborative but independent — you don’t wait to be told the next step
At Zopa we value flexible ways of working.
We value face-to-face collaboration and a good work-life balance. This hybrid role requires you to come to our London office 2-3 days a week.
You'll also have the option of working from abroad for up to 120 days a year!* But no matter where you are, we’ll make sure you’ve got everything you need to thrive, both in your work and home life, from day one.
*Subject to having the right to work in the country of choice
Diversity Statement
Zopa is proud to offer a workplace free from discrimination. Diversity of experience, perspectives, and backgrounds leads to better products for our customers and a unique company culture for our people. We are made up of nearly 50 nationalities, have a DE&I forum made up of Zopians wanting to make a difference and we are proud of our culture where everyone can bring their full self to work. Our approach to DE&I is reflected in our hiring process so please let us know if you require any reasonable adjustments.
Our approach to AI in interviews
At Zopa, AI isn't something we're testing out — it's part of how we work every day. As a proud partner of Jobs 2030, we're committed to building AI fluency across our workforce, and we expect Zopians to use AI as part of how they do their jobs.
Because of that, we want to be transparent about how we think about AI use during our hiring process.
Behavioural and competency-based interviews: please don't use AI. These conversations are designed to understand you — your experiences, your judgment, and how you've approached real situations. An AI-generated answer can't tell us that. What it can do is get in the way of us finding out whether we're the right fit for each other.
Technical interviews: it depends on the role. Some technical stages actively welcome AI use, others don't. Your Talent Partner will let you know what's expected at each stage. Where AI is part of the assessment, we'll be interested not just in the outcome, but in how you used it – the tools you chose, your reasoning, and the decisions you made along the way.
Zopa Bank London, England Office
Tooley Street, London, United Kingdom, SE1 2QG
