Product Analyst (Transaction Enrichment)

Analyze enrichment data (using Python and SQL) to understand where and why enrichment falls short - quantifying problems and building the evidence base for what's worth fixing.

Surface opportunities the team wouldn't otherwise see: patterns in the data that point to a product gap, a recurring failure mode that suggests a systemic fix, or a signal that something new is worth building.

Work out how a proposed solution should actually behave in practice - what inputs it needs, where it will struggle, what trade-offs exist between accuracy, cost, and coverage.

Build quick test harnesses to put a hypothesis in front of data before any engineering resource is committed.

Design and run evaluations - including LLM-as-judge approaches - to give the team real signal on whether a change improves things and where it introduces new problems.

Translate what you find into clear recommendations: what to build, why it matters, and what good looks like - so Product and Engineering can make confident decisions.

Keep up with developments in AI and data quality tooling - form a view on which new techniques are worth experimenting with in the enrichment context.

Comfortable writing code (typically Python and SQL) to explore data, clean outputs, call APIs, and prototype ideas.

Some experience working with LLM APIs: calling them, prompting them, structuring their outputs, and understanding why they sometimes give you nonsense.

You think in experiments: you form a hypothesis before looking at the data, design something that could prove you wrong, and interpret results with appropriate scepticism.

Naturally curious about messy, imperfect systems - you want to understand why something breaks, not just that it does, and brainstorm ideas to improve it.

You keep the product goal in view: you care about what changes for customers and the business.

Comfortable owning ambiguous problems: you can scope the work, prioritise what to test first, and know when good enough is actually good enough.

Clear communicator - you can explain what you built, what you found, and what it means to engineers, PMs, and stakeholders who don't care about the implementation details.

1-3 years in an analytical or technical role; experience in fintech, banking, or a fast-paced data-led environment is a plus but not required.

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!

About the Transaction Enrichment Team: The team sits at the heart of how Zopa turns data into intelligent products. We build and evolve the capabilities that transform raw transaction data into reliable, structured intelligence - so customers can understand their money better, and the rest of the business can build confidently on top of it.

A core focus is transaction enrichment: tagging merchants, assigning categories, ensuring data quality, and making sure everything integrates cleanly into our broader data models and customer-facing products.

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.