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Data Scientist (semantic Search/recommender Systems)

Data Scientist (semantic Search/recommender Systems)
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Data Scientist (semantic Search/recommender Systems)

Tesco UK
Welwyn Garden City
GBP 50 000 - 80 000
Description du poste
About the role

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.

About the Team

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 individual growth as experts in the field. Our team values work-life balance, team days, and cultivates a relaxed yet engaging culture.

What is in it for you

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. Benefits include:

  • 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 year's 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
Responsibilities
  • Applying, modifying, and designing algorithms and models for information retrieval and re-ranking; advising on systems architecture, Machine Learning components, and related 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
Minimum requirements
  • Experience as a Data Scientist or a PhD graduate with expertise in Semantic Search, recommender systems, information retrieval, or LLMs
  • PhD in Mathematics, Engineering, or Computer Science
  • Hands-on experience with Deep Learning approaches, including modern language models based on transformer architecture
  • Strong coding skills, preferably in Python, with a solid grasp of engineering practices such as version control, testing-driven development, and Continuous Integration
  • Desirable: Experience with Semantic Search, Vector Databases, and Search Engine frameworks, preferably Elasticsearch
About us

Our vision at Tesco is to become every customer's favourite way to shop, whether at home or on the go. Our core purpose is 'Serving our customers, communities and planet a little better every day'. We are committed to diversity, equity, and inclusion, ensuring everyone feels represented and can be themselves at work. We are proud to be accredited as a Disability Confident Leader and offer flexible working patterns, blending office and remote work to foster innovation and collaboration.

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* Le salaire de référence se base sur les salaires cibles des leaders du marché dans leurs secteurs correspondants. Il vise à servir de guide pour aider les membres Premium à évaluer les postes vacants et contribuer aux négociations salariales. Le salaire de référence n’est pas fourni directement par l’entreprise et peut pourrait être beaucoup plus élevé ou plus bas.

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