Data Scientist (Semantic Search/Recommender Systems)

As a Data Scientist within Semantic Search, you will influence the search experience on the Tesco website by utilising advanced technologies and collaborating with a team of seasoned Data Scientists, Machine Learning Engineers, and Software Engineers. This role is based out of our London (Farringdon) office, offering the flexibility of hybrid working. Spend three days a week in the office and the remainder working from home.

Join our world-class team of data professionals who are passionate about solving sophisticated business problems and deploying data products at scale. Our team works across various areas of our business, personalising our customers' experience across all touchpoints, both online and in-store. We are committed to personal and career development, providing on-desk training, support, and dedicating 10% of your working week to learning and professional growth. Additionally, there are opportunities to attend and speak at external and internal events, encouraging individuals growth as experts in the field. Our team values work-life balance, team days, and cultivates a relaxed yet engaging culture.

We’re all about the little helps. That’s why we make sure our Tesco colleague benefits package takes care of you - both in and out of work.

• Annual bonus scheme of up to 20% of base salary
• Holiday starting at 25 days plus a personal day (plus Bank holidays)
• Private medical insurance
• 26 weeks maternity and adoption leave (after 1 years' service) at full pay, followed by 13 weeks of Statutory Maternity Pay or Statutory Adoption Pay
• 4 weeks fully paid paternity leave
• Free 24/7 virtual GP service, Employee Assistance Programme (EAP) for you and your family, free access to a range of experts to support your mental wellbeing

You will be responsible for:

• Applying, modifying, and designing algorithms and models for information retrieval and re-ranking
• Advising on the systems architecture, Machine Learning components, and associated technologies
• Using data to train and fine-tune models
• Developing efficient and high-quality code in Software Engineering
• Collaborating closely with Search Engineers, ML Engineers, and Data Scientists
• Promoting data science internally and effectively communicating sophisticated solutions to non-technical colleagues

You will need:

• An experienced Data Scientist or a PhD graduate with Semantic Search, recommender systems or information retrieval or LLM experience.
• PhD in a relevant field such as Mathematics, Engineering or Computer Science
• Hands-on expertise with Deep Learning approaches, including modern language models based on transformer architecture
• Strong coding skills, preferably in Python and a solid grasp of effective methods in Engineering, including version control, development driven by testing, and Continuous Integration
• Desirable: Experience with Semantic Search approaches and Vector Databases combined with experience of working with Search Engine frameworks, preferably Elasticsearch

Our vision at Tesco is to become every customer’s favourite way to shop, whether they are at home or out on the move. Our core purpose is "Serving our customers, communities and planet a little better every day". Serving means more than a transactional relationship with our customers. It means acting as a responsible and sustainable business for all stakeholders, for the communities we are part of and for the planet. Diversity, equity and inclusion (DE&I) at Tesco means that whoever you are and whatever your background, we always want you to feel represented and that you can be yourself at work. In short, we’re a place where Everyone’s Welcome. We’re proud to have been accredited Disability Confident Leader and we’re committed to providing a fully inclusive and accessible recruitment process. We’re a big business and we can offer a range of diverse full-time & part-time working patterns across our many business areas, which means that we can find something that works for you. We work in a more blended pattern - combining office and remote working. Our offices will continue to be where we connect, collaborate and innovate.