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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior Data Scientist - Business Operations - **Company:** Deliveroo - **Location:** London, UK - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** A/B Testing, Data Analysis, Python (Programming Language), SQL Databases, Tableau (Software), Scripting, Data Analytics, Looker Analytics - **Published:** September 1, 2026 - **Apply:** https://www.totaljobs.com/job/senior-data-scientist/deliveroo-job107930618 ## About the Role Our ideal candidate brings strong expertise in some of these areas and the curiosity to grow in others: * Experience in an analytical or data science role, such as data analytics, data science, forecasting, planning, strategy analytics, or a similar discipline. Experience in logistics, e-commerce, marketplaces, or another fast-moving, customer-focused business is useful but not essential. * Proficiency with SQL and a scripting language such as Python or R, alongside experience with BI or visualisation tooling such as Looker, Tableau, or similar. * Comfortable using modern AI-assisted tools to work efficiently while maintaining high standards of accuracy and reproducibility. * A pragmatic approach to problem-solving: you can balance analytical rigour with speed, adapt your approach to the importance of the decision, and focus effort where it will have the greatest impact. * Effective problem-solving: you can take an ambiguous question, identify the underlying problem or decision, develop hypotheses, and use data and business context to reach a clear point of view. * Experience with experimentation and/or causal inference is a strong plus: the ability to unpick insights and steer strategic decisions. * Excellent communication skills, in person, in writing, and in code, with the ability to translate business needs into analytical problems and complex findings into simple recommendations. * Driven, hard-working, and agile. BizOps sits at the centre of a fast-growing business; we move quickly to scale at pace. * London-based, with a minimum of three days per week in the office. ## Description Deliveroo is hiring a Senior Data Scientist to join BizOps, based in our London HQ (hybrid, minimum three days per week in the office). This role is largely project-based: starting from a strategic or performance question, you'll combine data, business context, and structured problem-solving to provide the insights that drive decision-making at a global level with senior stakeholders. You will own delivery end-to-end, from the messy, ambiguous question to a rigorous, trustworthy, and actionable answer. You'll be equally comfortable building the systems that make performance visible and going deep on the investigations that explain it. One week you might diagnose why a key market has moved away from plan; the next, identify the drivers behind a change in customer or operational performance; the next, build monitoring that helps teams spot and understand emerging issues earlier. Success in this role requires building effective working relationships across Deliveroo, particularly with international markets, as well as the Data Science, Operations, Commercial, and Finance teams. What You'll Be Doing * Answer the questions that matter, continuously. Maintain a rigorous view on business performance: Are we on track against our goals? What's changed? How does this compare with what we expected? What should we expect next? Then go further: Why is it happening, what matters most, and what should we do about it?" * Own delivery end-to-end. Independently identify, define, and deliver impactful work aligned with business goals, operating with minimal guidance to ship fast, high-quality solutions. * Navigate ambiguity. Deconstruct broad, ambiguous problem spaces into structured analytical roadmaps, and understand how your work intersects with adjacent systems and teams. * Build for scale, not one-offs. Build the pipelines, models, dashboards, monitoring, and investigative tooling that make performance visible and reliable. Automate wherever possible; redoing analyses by hand is slow and error-prone. * Measure impact with discipline. Design measurement strategies from simple A/B tests to quasi-experimental designs (synthetic control, difference-in-differences, event studies) when trials aren't feasible, always with conservative, assumption-explicit language. * Be a first responder. Surface deviations before they become escalations, and be just as willing to give the confident 'this is noise, no action needed' as the alarm. * Communicate to influence. Translate complex findings into clear, simple, actionable recommendations for both technical and non-technical audiences that shape roadmaps and decisions. * Raise the bar. Contribute to the broader Analytics community, improve shared approaches and best practices, and help build data literacy across the business. ## Related Videos - [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail) - [JavaScript? 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