Location
London - Hybrid Working

Hours
Full Time

Salary
Negotiable

About the Role
We are Ocado Group, bringing world-class automation to online grocery through our Ocado Smart Platform (OSP), which combines cutting-edge robotics, AI, and IoT within advanced Customer Fulfilment Centres (CFCs). As a Senior Data Scientist in our Autoplanner team, you will develop AI-powered systems that unify planning across global warehouses and last-mile operations. You will build machine learning models, optimisation algorithms, and operational simulations that underpin our core planning products. Your work will take high-impact models from concept to monitored production systems, ensuring automated operational plans are robust, globally optimised, and trusted across international supply chains. Collaborating closely with software engineers and product managers, you will set technical direction for key initiatives and mentor colleagues to elevate the team’s data science capabilities. You will also engage with internal and external stakeholders, including global retail partners, translating complex logistics challenges into production-ready data science solutions and shaping the future of autonomous operational planning.

Key Responsibilities
- Deliver machine learning models for planning products, iterating from prototype to production artefacts
- Explore innovative modelling and optimisation approaches, benchmarking rigorously against existing solutions
- Build and extend simulations of warehouse operations and customer demand to validate live operational plans
- Define and measure business-critical metrics using robust statistical techniques
- Set technical direction and delivery strategy for data science initiatives
- Mentor and develop the technical capabilities of data scientists
- Partner with software engineers to ensure models are cleanly packaged, deployed, monitored, and efficiently served
- Manage relationships with product managers, internal teams, and external retailers to align requirements and delivery roadmaps

Experience
- Proven track record of taking data science and machine learning models into production and maintaining them
- Strong machine learning and statistical expertise with rigorous model performance evaluation
- Fluency in writing production-quality Python code
- Experience working with large datasets in cloud data warehouses such as BigQuery, including data-quality checks
- Experience building simulations or stochastic models of operational systems
- Practical experience using AI coding agents with critical judgement to verify generated code
- Demonstrated ability to collaborate effectively with software engineers, product managers, and business stakeholders

About You
- Innovative and proactive with strong problem-solving skills
- Able to mentor and lead technical initiatives
- Comfortable working in a fast-paced, cross-functional environment
- Passionate about applying data science to real-world logistics and supply chain challenges

Nice to Haves
- Experience with mathematical optimisation frameworks such as OR-Tools
- Experience with discrete-event simulation libraries such as SimPy
- Background or domain knowledge in logistics, supply chain, or operational research

Qualifications
No specific qualifications required; emphasis is on proven experience, technical skills, and a collaborative mindset.