Data Analyst

• Answer the commercial questions the business is deciding on - acquisition efficiency, retention and lifetime value, pricing, promotions, product launches, channel mix - starting from the recommendation, not the chart.
• Publish a substantial piece of analysis every month, naming the decision it informs and the value at stake.
• Act as the embedded analyst for a part of the business (most likely Growth and Retention, plus marketplaces), close enough to know what’s coming before it lands as a request.
• Design and read measurement: hypotheses, control groups, duration and decision rules agreed before launch, with results logged back to the warehouse rather than left in a vendor tool.
• Build and maintain the dashboards the business runs on, from specification through to production, and model data in BigQuery using Dataform.
• Own our core metric definitions and keep them consistent - one definition, one implementation, one owner - and reconcile to source systems to catch issues before stakeholders do.
• Review AI-generated code, your own and others’, before it ships.
• Enable self-serve across the business: warehouse and AI access, metric and dashboard catalogues, training.

• 3-5 years in analytics in a D2C, eCommerce or high-growth environment.
• Commercial fluency - comfortable with contribution margin, CAC and payback, cohort retention and lifetime value, and able to hold your own with a CFO or growth lead on what a number means for the P&L.
• Strong SQL and experience with a modern cloud warehouse (BigQuery preferred) and a layered modelling tool (Dataform or dbt).
• Genuinely AI-native: you already work with AI coding and analysis tools daily, can write a specification an agent can follow, and review its output sceptically rather than shipping it (we use Claude and Claude Code currently but are happy to experiment).
• Able to review code you didn’t write and spot a logic or data quality error before it reaches a dashboard; comfortable in Git/GitHub day to day and with enough Python to read, debug and extend existing scripts.
• Experimentation literacy - you know what makes a result trustworthy and have the confidence to say a test can’t be read.
• Curiosity and pragmatism: fast to a directionally correct answer, with the judgement to know when exact is required, and excellent written communication for a remote, senior audience.

• Time to recharge - 25 days annual leave (plus bank holidays) to reset, relax and adventure
• Health & dental cash plan - Everyday health and dental bills covered, because looking after our people comes first
• Core hours / Hybrid working - Our set office days are Monday, Wednesday and Friday, with core hours of 10am-4pm.
• Dog friendly office - Obviously! Bring your pup to work with you.
• Remote working - Fancy a change? Work from anywhere (time-zone permitting) for two weeks in summer and two weeks in winter
• Bike to work scheme - Ditch the commute stress and cycle to work
• Enhanced family leave - More support for life’s important moments and milestones
• Pension scheme - Enroll in the Wuffes pension scheme

If you require any reasonable adjustments during the recruitment process, please do not hesitate to contact us - we will always be happy to help.

As a Data Analyst at Wuffes, you’ll be the analyst the business brings its commercial questions to - turning data into the answers that drive decisions. You’ll partner with Growth, Marketplace, Finance, Digital Product and CX on what to test, what it’s worth, and whether it worked, and publish a substantial piece of analysis every month that names the decision it informs. The dashboards and data models that make those answers repeatable are yours too, but they’re the means, not the point.

You’ll work in our own codebase rather than a BI tool. In early 2026 we moved off our previous BI tool onto self-hosted dashboards we build ourselves, hosted on Google Cloud Platform (GCP) and backed by BigQuery and Dataform. It’s AI-first: you write the spec, Claude Code writes most of the code, and you review, validate and ship it.