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ocadogroup

Senior Data Scientist

London Posted today

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Skills this job asks for

Machine learningLogisticsWarehouse operationsStatisticsPythonSupply chain

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Sponsorship verdict

No sponsorship evidence yet

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  • No government sponsor record hereThis employer posted directly and does not match a government sponsor register.
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  • Can’t check pay against the visa rulesNo salary stated. UK Skilled Worker visa needs at least £41,700 a year (new-entrant (under 26, recent Student/Graduate visa) or STEM PhD: £33,400).
  • Confirmed live todayWhen a source last listed this job as open.
Details and sources
Can’t check pay against the visa rules
No salary stated. UK Skilled Worker visa needs at least £41,700 a year (new-entrant (under 26, recent Student/Graduate visa) or STEM PhD: £33,400). Source: https://www.gov.uk/skilled-worker-visa/when-you-can-be-paid-less, rules effective 2025-07-22.

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Before you apply

Sponsorship unknown

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About the role

Senior Data Scientist | Autoplanner | Hybrid Working | London Introduction: We are Ocado Group, and we're bringing world-class automation to online grocery. Our Ocado Smart Platform (OSP) combines cutting-edge robotics, AI, and IoT within our advanced CFCs (Customer Fulfilment Centres). We've mastered the single pick, transforming online delivery for our global partners. Join us and be part of a team pushing the boundaries of retail technology. About the Role: As a Senior Data Scientist within our Autoplanner team, you will build AI-powered systems that unify planning across global warehouses and last-mile operations. You will be responsible for developing the machine learning models, optimisation algorithms, and operational simulations that underpin our core planning products. By taking high-impact models from concept through to monitored production systems, you will ensure automated operational plans are robust, globally optimised, and trusted to run live across our partners' international supply chains. Working closely with cross-functional software engineers and product managers, you will set the technical direction for key initiatives while mentoring colleagues to elevate the team’s overall data science capabilities. You will also engage directly with internal and external stakeholders, including global retail partners - to translate complex logistics challenges into production-ready data science solutions, shaping the future of autonomous operational planning. Key Responsibilities: • Deliver machine learning models for planning products, iterating from initial prototype to evaluated and monitored production artefacts. • Explore innovative modelling and optimisation approaches, benchmarking and testing them rigorously against existing solutions. • Build and extend simulations of warehouse operations and customer demand to validate and power live operational plans. • Define and measure business-critical metrics using robust statistical techniques, establishing the team's standards for model evaluation. • Set the technical direction and delivery strategy for the data science initiatives you lead. • Develop the technical capabilities of data scientists across the team through mentoring, technical guidance, and collaboration. • Partner with software engineers to ensure models are cleanly packaged, deployed, monitored, and efficiently served on the platform. • Own relationships with product managers, internal partner teams, and external retailers to align on requirements and delivery roadmaps. What We’re Looking For: Essential • Proven track record of taking data science and machine learning models into production, maintaining them, and leading initiatives end-to-end. • Strong machine learning and statistical expertise, including the ability to evaluate model performance rigorously against business metrics. • Fluency in writing production-quality Python code. • Experience querying and working with large datasets in cloud data warehouses such as BigQuery, including implementing data-quality checks. • Experience building simulations or stochastic models of operational systems. • Practical experience using AI coding agents, alongside the critical judgement to verify and test generated code and outputs. • Demonstrated ability to collaborate effectively with software engineers, product managers, and diverse business stakeholders. Nice to Haves • Experience with mathematical optimisation frameworks and toolkits, such as OR-Tools. • Experience with discrete-event simulation libraries, such as SimPy. • Background or domain knowledge in logistics, supply chain, or operational research. Benefits We believe in supporting our people with meaningful, flexible benefits that prioritise well-being and work-life balance

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