Senior Product Analyst, Transaction Enrichment

Zopa Bank

. Analyse enrichment data using Python and SQL to understand where and why enrichment falls short .

Posted 9/18/2026full-timeLondon • United KingdomSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Proficient in Python and SQL for data analysis and problem-solving, with a strong focus on product-oriented thinking and the ability to communicate findings effectively to cross-functional teams. Experienced in evaluating AI-driven solutions and enhancing transaction enrichment capabilities.

Highest-signal resume keywords

Python ProgrammingSQL Data AnalysisLLM API ExperienceProduct-Oriented ThinkingExperimental Mindset

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Hard Skills

Data AnalysisCode PrototypingHypothesis TestingData CleaningAPI Integration

Soft Skills

Clear CommunicationCuriosityProblem Ownership

Tools & Technologies

AI ToolsData Quality Tooling

Industry Keywords

FintechBankingData-Led Environment

Tech Stack

Tools & technologies

PythonSQL

About the role

Key responsibilities & impact

Analyse enrichment data using Python and SQL to understand where and why enrichment falls short
Quantify problems and build evidence for potential fixes
Surface product opportunities, recurring failure modes, systemic fixes, and signals for new products
Determine how proposed solutions should behave, including inputs, limitations, and accuracy, cost, and coverage trade-offs
Build quick test harnesses to test hypotheses before engineering resources are committed
Design and run evaluations, including LLM-as-judge approaches
Translate findings into recommendations for Product and Engineering
Monitor developments in AI and data quality tooling and assess techniques for transaction enrichment
Understand shortcomings in AI-driven transaction enrichment and shape future product development
Work closely with the Product Manager and Engineering to integrate findings into the roadmap and real product changes
Improve transaction enrichment capabilities, including merchant tagging, category assignment, data quality, and integration with data models and customer-facing products

Requirements

What you’ll need

Comfortable writing code, typically Python and SQL, to explore data, clean outputs, call APIs, and prototype ideas
Some experience working with LLM APIs, including calling them, prompting them, structuring outputs, and understanding limitations
Experimental mindset: form hypotheses, design tests, and interpret results skeptically
Curiosity about messy, imperfect systems and diagnosing failures
Product-oriented thinking focused on customer and business impact
Comfortable owning ambiguous problems, scoping work, prioritizing tests, and judging when work is good enough
Clear communication with engineers, PMs, and stakeholders
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

Benefits

Comp & perks

Flexible ways of working
Hybrid working arrangement
Option to work from abroad for up to 120 days a year, subject to having the right to work in the country of choice
Support and equipment to thrive in work and home life from day one
Workplace free from discrimination
Reasonable adjustments during the hiring process