Hybrid opportunity at
ZopaProduct Analyst (Mid and Senior Level) - Transaction Enrichment
Zopa is recruiting a Product Analyst for its Transaction Enrichment team in London. The posting title covers mid and senior levels, but the core need is…
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About This Role
Zopa is recruiting a Product Analyst for its Transaction Enrichment team in London. The posting title covers mid and senior levels, but the core need is for an analyst who combines data work with product judgement. The team tags merchants, assigns spending categories and checks data quality, so that transaction data can be trusted by Zopa's products and wider data models. The analyst looks into where the AI-driven enrichment underperforms,…
Job Description
Zopa is recruiting a Product Analyst for its Transaction Enrichment team in London. The posting title covers mid and senior levels, but the core need is for an analyst who combines data work with product judgement. The team tags merchants, assigns spending categories and checks data quality, so that transaction data can be trusted by Zopa's products and wider data models.
The analyst looks into where the AI-driven enrichment underperforms, forms hypotheses and builds small prototypes to test them before engineering time is committed. Typical work involves analysing enrichment output with Python and SQL, measuring weak spots, and noticing patterns that suggest product gaps or a systemic fix. The analyst designs evaluations, including LLM-as-judge methods, to show whether a change helps and where it creates new problems, then recommends what to build and what good performance looks like. The role also keeps an eye on newer AI and data-quality techniques worth trying. It is an applied rather than research post: the analyst must move quickly, make pragmatic trade-offs and focus on what reaches customers. The post is hybrid, with two to three days a week in the London office.
Suited to an analyst with one to three years in an analytical or technical role, who can write SQL or Python, has worked with LLM APIs, and approaches problems through hypotheses and experiments.
Responsibilities
- Use Python and SQL to find where and why enrichment falls short, and size each problem.
- Identify patterns that reveal product gaps, recurring failure modes or signals worth building.
- Work out how a proposed fix should behave, including its inputs, weak points and trade-offs among accuracy, cost and coverage.
- Build lightweight test harnesses to check a hypothesis before engineers are involved.
- Design and run evaluations, including LLM-as-judge methods, to measure impact.
- Turn findings into recommendations for Product and Engineering on what to build and why.
- Keep track of AI and data-quality tooling and recommend which techniques to try.
Requirements
- Able to write SQL or Python to explore data, clean outputs, call APIs and prototype, or willing to learn Python with AI-assisted tools.
- Some hands-on experience calling and prompting LLM APIs and structuring their outputs.
- Forms a hypothesis before looking at data and designs tests that could prove it wrong.
- Curious about messy systems and keen to learn why they fail.
- Can scope open-ended work, decide what to test first and know when results are good enough.
- Explains findings clearly to engineers, product managers and non-technical stakeholders.
- One to three years in an analytical or technical role.
Qualifications
- Fintech, banking or another fast-paced, data-led background.
Core Skills
Benefits
- Flexible working, including the option to work from overseas for as many as 120 days a year, subject to the right to work in that country.
Frequently Asked Questions
Answers are based only on the employer’s listing; where it doesn’t say, neither do we.
Where is this role based?
The role is based in London and is hybrid, with office attendance two to three days a week.
What experience is needed?
The posting asks for one to three years in an analytical or technical role. Fintech experience is a plus but not required.
Which skills does the role use?
SQL and Python for data analysis, plus experience with LLM APIs and designing evaluations, including LLM-as-judge methods.
Is a salary stated?
No. The posting does not specify a salary.
Sample Interview Questions
AI-generated questions tailored to this specific role — a preview of the full practice set.