Senior Product Analyst (Transaction Enrichment) at Zopa in London

Job description

• We’re looking for a Senior Product Analyst to join our Transaction Enrichment team. At heart this is a data and analytical role — but one where strong product thinking matters as much as technical ability. You'll be expected to care not just about what the data shows, but about what should change as a result.
• You'll spend your time understanding where our AI-driven transaction enrichment falls short, forming hypotheses, building prototypes to test them, and shaping what we build next. This isn't a research role - you'll be expected to move quickly, make pragmatic trade-offs, and care about what ships and what lands, not just what looks good in a notebook.
• You'll be comfortable writing code and using LLM APIs directly. You won't be starting from scratch every time - AI coding tools are part of how we work, but you'll need the underlying capability to use them well.
• Your output is insight and evaluation — shaping what we build and the implementation decisions behind it: which prompts work, how data should be processed, where the trade-offs lie. You'll work closely with the Product Manager and Engineering to ensure your findings land in the roadmap and translate into real changes.

Responsibilities

• Analyse 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

Requirements

• 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

Skills

Required

• Python
• SQL
• LLM APIs
• Data analysis
• Prototyping
• Hypothesis testing
• Product thinking
• Communication

Preferred

• Fintech or banking experience