SlipstreamJobs tracks this role from the company's public career site. Apply directly on the employer's site.
Zopa is a fintech company founded in 2005 as the first peer-to-peer lending platform, now operating as Zopa Bank—a customer-centric digital bank challenging traditional finance. This Senior Product Analyst role focuses on transaction enrichment, a critical capability for understanding and improving how Zopa's systems classify and enhance transaction data.
In this role, you will analyze enrichment data using Python and SQL to identify gaps and failures in enrichment quality, quantifying problems and building evidence for prioritization. You'll surface non-obvious patterns in data that reveal product gaps, recurring failure modes, or opportunities for new capabilities. You'll work out how proposed solutions should behave in practice—understanding inputs, failure modes, and trade-offs between accuracy, cost, and coverage. You'll build quick test harnesses to validate hypotheses before engineering commits resources, and design evaluations (including LLM-as-judge approaches) to measure whether changes improve outcomes and identify new problems. Finally, you'll translate findings into clear recommendations for Product and Engineering teams, and stay current with developments in AI and data quality tooling to identify techniques worth experimenting with.
You'll work in a hybrid model, coming to the London office 2–3 days per week, with flexibility to work abroad up to 120 days annually (subject to work authorization). Zopa values collaboration, work-life balance, and diversity—the company comprises nearly 50 nationalities and emphasizes bringing your full self to work.
Requirements:
- Comfortable writing code in Python and SQL to explore data, clean outputs, call APIs, and prototype ideas
- Some experience working with LLM APIs: calling them, prompting them, structuring outputs, and understanding failure modes
- Experimental mindset: form hypotheses before examining data, design tests that could prove you wrong, interpret results with skepticism
- Naturally curious about messy, imperfect systems; want to understand why things break and brainstorm improvements
- Keep product goals in view; care about customer and business impact
- Comfortable owning ambiguous problems; can scope work, prioritize what to test first, and recognize when good enough is sufficient
- Clear communicator who can explain findings and implications to engineers, PMs, and non-technical stakeholders
- 1–3 years in an analytical or technical role; experience in fintech, banking, or fast-paced data-led environments is a plus but not required
