Product Analyst

• Deliver innovative risk technology solutions aligned with European Central Bank supervisory expectations
• Translate regulatory and business requirements into user stories, functional specifications, and acceptance criteria
• Drive testing and rollout in Agile delivery cycles
• Execute gap analyses and support horizontal reviews
• Address ECB findings regarding risk taxonomies, RCSA, KRIs, and ICAAP/OR capital
• Strengthen operational risk frameworks across RCSA, loss data collection, and scenario analysis
• Advance data quality, governance, and lineage initiatives
• Partner with 1LOD, 2LOD, IT, Compliance, Finance, and Audit
• Deliver cohesive risk tools, user training, and change management strategies
• Report directly to the Credit Risk Tech Lead, with a dotted line to the Head of Credit Risk

Operational Risk Product Analyst

• Partner with Product Managers, Designers, Engineers, and Analysts across Zopa to deliver trusted insights for decisions and improve the Joint Account product
• Design and evaluate statistically rigorous experiments to support rapid, iterative product development
• Define metrics serving as the source of truth for product performance, user experience quality, and progress on key results
• Own the analytics roadmap, identify analysis opportunities, and prioritize high-impact work
• Develop AI-enabled analytics tools for natural-language insight generation and internal data applications
• Develop a detailed understanding of customers and how they use the account
• Guide product development toward innovative features and experiences
• Own customer outcomes
• Communicate insights to stakeholders at all levels, including managers and leadership

Product Analyst, Mid and Senior Level

• Own instrumentation coverage for the AI pillar by defining required events and properties and driving implementation with product managers and engineering
• Define feature-level KPIs and success metrics for Voice AI, Conversation AI, AI Employee, and Ask AI
• Partner with the Experimentation & Causal Inference lead to design and interpret AI experiments, including approaches for non-deterministic systems
• Distinguish real signal from instrumentation gaps, novelty effects, and data maturity
• Set measurement direction, canonical metrics, instrumentation standards, and contracts for the AI analytics domain
• Mentor analysts as the team grows
• Translate findings into recommendations for AI product managers and influence the roadmap
• Flag data gaps to Analytics Engineering and help shape event taxonomy
• Use AI tooling such as Claude for exploration, documentation, and analysis
• Establish measurable instrumentation coverage, trusted feature-level KPIs, segmented adoption and quality analysis, rigorous experiment reads, and an analytics foundation for future analysts

Lead Product Analyst – AI Products

• 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

Senior Product Analyst, Transaction Enrichment

• Partner with Engineering to define and maintain event taxonomy, tracking standards, and instrumentation quality
• Build and maintain scalable, self-service dashboards for product teams
• Establish and document clear metric definitions as a shared source of truth
• Improve measurement as the product evolves
• Use AI to generate insights and recommendations from product signals
• Ensure accurate and accessible reporting across the product analytics stack
• Build and maintain dbt models for core product entities and behaviors
• Contribute to a clean, usable metric layer for business stakeholders
• Structure and analyze Voice of the Customer inputs from support, churn, NPS, sales feedback, and customer interviews
• Support data quality through testing, monitoring, documentation, and automation
• Deliver recurring product analytics reporting covering adoption, engagement, and retention
• Present analytics readouts to business stakeholders and executives with findings and recommendations
• Analyze connections between product behavior, revenue, and retention outcomes
• Support automated reporting and AI-assisted workflows while maintaining metric integrity
• Build analytics and customer insights that inform roadmap and investment decisions

• Partner with Engineering to define and maintain event taxonomy, tracking standards, and instrumentation quality
• Build and maintain scalable, self-service dashboards for product teams
• Establish and document clear metric definitions as a shared source of truth
• Improve how and what is measured as the product evolves
• Use AI to derive insights and recommendations from product signals
• Ensure accurate and accessible reporting in the product analytics stack
• Build and maintain dbt models for core product entities and behaviors
• Contribute to a clean, usable metric layer for business stakeholders
• Structure and analyze Voice of the Customer inputs, including support, churn, NPS, sales feedback, and customer interviews
• Support data quality through testing, monitoring, documentation, and automation
• Use AI tooling to improve data capabilities
• Deliver recurring product analytics reporting on adoption, engagement, and retention
• Present analytics readouts to business stakeholders and executives with findings and recommendations
• Analyze connections between product behavior, revenue, and retention outcomes
• Support automated reporting and AI-assisted workflows while maintaining metric integrity
• Make insights and reporting automated and self-service using emerging AI techniques

Product Analyst jobs in United Kingdom

Operational Risk Product Analyst

Product Analyst, Mid and Senior Level

Lead Product Analyst – AI Products

Senior Product Analyst, Transaction Enrichment

Product Analyst

Product Analyst, Romania