ABOUT US:

Ocado Technology is putting the world’s retailers online using the cloud, robotics, AI, and IoT. We develop the innovative software and systems that power Ocado.com, the world’s largest online-only grocery retailer as well as the global ’Ocado Smart Platform’. With everything from websites to fully autonomous warehouse that we design in-house, our employees need to be specialists in a wide range of technologies to help drive our business. We champion a value-led culture to get our teams working at their very best and to help create a collaborative working environment that our people love. Core values of Trust, Autonomy, Craftsmanship, Collaboration and Learn Fast help drive our innovative culture

The Supply Chain Scientist brings deep domain expertise in eCommerce and Supply Chain, combined with advanced analytics and modelling skills, to help shape and influence the development of the Ocado Smart Platform (OSP).
This role is both strategic and hands-on: working across a range of stakeholders and often directly with Partners to understand their operations—through data, conversations, and collaboration with Partner Success teams. The Data Scientist identifies opportunities to improve supply chains and product ranges, draws out key insights, and generalises learnings that can benefit all Partners.

By working closely with Product Managers, the Analyst helps embed these insights into OSP—building impactful, data-driven decision support tools that enhance partner outcomes and strengthen the platform’s overall capability. Role and responsibilities will include:

• Strategic Contribution: Use domain knowledge and advanced analytics to influence the Supply Chain/Analytics & Insight product strategy and roadmap, ensuring data-driven decision support is embedded within key initiatives
• Analytical and Modeling Leadership: Design, develop, and implement modeling and optimisation techniques to address complex Supply Chain challenges, such as reducing supply chain costs, improving automated planning decisions, reducing substitution, optimising range, or minimising waste
• Prototype and Testing: Explore opportunities for new models and tools, building prototypes and estimating business benefits. Conduct testing and measure impact on KPIs to refine models for deployment
• Collaboration Across Teams: Work with Product Managers, Data Engineers, Data Scientists, and other stakeholders to integrate models and tools into OSP, ensuring user-friendly, scalable solutions for retail partners. Act as the representative of the broader Data Org within the Supply Chain Analytics & Insight Product Area
• Mentorship and Knowledge Sharing: Mentor and guide junior analysts, sharing insights from both a domain and analytical perspective to uplift the team’s capabilities
• Explore AI for Supply Chain Decision-Making: Investigate and experiment with generative AI and other emerging technologies to enhance data-driven decision-making within the Supply Chain and Analytics domain
• Impact Measurement: Regularly assess the impact of deployed solutions, ensuring alignment with business objectives and optimising for long-term value