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Tech Stack
Tools & technologiesBigQueryCloudPythonSQL
About the role
Key responsibilities & impact- Be the data voice in your squad.
- Bring data into planning, refinement, reviews, and decision-making from the start.
- Understand your users. Analyse customer journeys to identify friction, drop-offs, retention drivers, and feature opportunities.
- Commercial sense. Connect squad work to P&L outcomes, including conversion, retention, and margin.
- Define success metrics with your PM. Set clear metrics, targets, and dashboards to track feature performance.
- Art of the possible & POC mock-ups. Create fast, lightweight demos to show how data and AI could improve the customer experience.
- Build product features and data products. Develop production-ready, data-driven features that customers interact with.
- Experimentation rigour. Lead A/B tests, holdouts, sample sizing, and post-test analysis to support confident decisions.
- Own certified metrics and the semantic layer for your squad’s domain. Ensure metrics are consistent, documented, accessible, and trusted.
- Applied AI as a working tool. Use LLMs and AI tools to speed up analysis, prototype ideas, and support AI-augmented features.
- Data storytelling that drives action. Turn technical work into clear recommendations with Product for wider stakeholders.
- Contribute to the function. Share learnings through the Community of Technical Practice and help raise data and AI fluency across MPB.
Requirements
What you’ll need- You're a senior data professional focused on turning data into decisions and product outcomes, with a technical lean into either data engineering or data science.
- You're comfortable using everything from traditional regression to generative AI, and genuinely curious about the parts of the stack you haven't yet mastered.
- You are curious in nature and value pragmatic innovation over academic purity - finding the fastest, most robust path to value.
- You are a natural collaborator who wants to move beyond ‘servicing tickets’ to co-creating the future of agentic commerce.
- Demonstrated experience in a hands-on data role, ideally in e-commerce, marketplace, or product-led tech.
- Strong SQL and working Python or R for statistical modelling, analysis and lightweight prototyping.
- Comfort with the modern data stack - a cloud warehouse (BigQuery or equivalent) and dashboard design principles.
- Solid grasp of statistics and experimental design - hypothesis testing, sample sizing, A/B testing rigour in a consumer-facing context.
- Strong product sense and commercial instinct - you can connect work to P&L outcomes and defend value trade-offs.
- Active practitioner of applied AI / LLM tooling in your analytics or prototyping workflow.
- Excellent storytelling - credible into senior commercial stakeholders.
Benefits
Comp & perks- 25 days annual leave
- 1 wellbeing day off per year
- 5% employer contributory pension scheme
- Private healthcare
- Access to EAP with a range of employee discounts
- Buzzing social calendar
- Dog friendly workplace
- Bespoke Learning Management System - the MPB 'Learning Lab' with access thousands of free courses to upskill in any areas you'd like; whether personally or professionally
- 2 volunteer days per year for charity which aligns with MPB values, and of your choosing
ATS Keywords
✓ Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
data analysisA/B testingstatistical modelingdata engineeringdata scienceSQLPythonRexperimental designapplied AI
Soft Skills
collaborationcuriositypragmatic innovationstorytellingcommercial sensedata fluencydecision-makingcommunicationleadershipproblem-solving