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Deliveroo, now part of DoorDash, is seeking a Senior Data Scientist to join the Business Operations (BizOps) team in London. The BizOps team serves as the analytical backbone of the business, transforming raw operational and financial data into actionable intelligence for operators, executives, and functional teams.
In this role, you will own end-to-end analytical projects that drive strategic decision-making at a global scale. You'll work on a diverse range of challenges: diagnosing why key markets deviate from plan, identifying drivers of customer and operational performance changes, and building monitoring systems that help teams spot emerging issues early. Your work spans the full analytics stack—from warehouse models and data pipelines to dashboards, monitoring systems, and deep-dive investigations.
Key responsibilities include:
- Continuously monitoring business performance against goals, plans, and expectations, then investigating root causes and implications
- Independently identifying, defining, and delivering impactful analytical work with minimal guidance
- Deconstructing ambiguous business problems into structured analytical roadmaps
- Building scalable pipelines, models, dashboards, and monitoring tools rather than one-off analyses
- Designing rigorous measurement strategies, from A/B tests to quasi-experimental designs (synthetic control, difference-in-differences, event studies)
- Acting as a "first responder" to performance deviations, surfacing signals before they escalate
- Translating complex findings into clear, actionable recommendations for technical and non-technical stakeholders
- Contributing to the broader analytics community and raising data literacy across the organization
You'll work closely with international markets, Data Science, Operations, Commercial, and Finance teams. The culture is informal, fast-paced, and entrepreneurial, with opportunities for rapid progression given the business scale and senior stakeholder exposure.
Required expertise: strong analytical or data science background (analytics, data science, forecasting, planning, or strategy analytics); proficiency in SQL and Python/R; experience with BI/visualization tools (Looker, Tableau, or similar); pragmatic problem-solving balancing rigor with speed; comfort with modern AI-assisted tools. Experience in logistics, e-commerce, or marketplaces is valuable but not essential.
