Job description

Building the next-generation grocery ecommerce suite that´s changing the way the world shops

At Ocado Technology, we’re an ambitious global company completely transforming the way the world shops with our cutting-edge AI, ML and robotic technology. With our retail partners spanning the globe, there’s a huge amount of growth and opportunity.

The e-commerce stream plays a key role in offering frictionless, convenient, and hyper-personalised shopping experiences for millions of global users across multiple platforms, in different regions, languages, currencies, and more.

Based in our Barcelona office in the heart of the 22@ hub, this amazing community of 27+ nationalities offers an unparalleled culture focused on growth and learning.

Get to know us:

Job Purpose

Data Science is responsible for designing cutting-edge machine learning and optimisation techniques to convert data into important business insights and solutions.

We focus on machine learning and optimisation problems across Ocado’s E-commerce - from recommending products to customers, to search optimisation and intelligent substitutions. Our data is stored in Google BigQuery, we work primarily in Python for machine learning and use frameworks such as Spark and TensorFlow. We are looking for someone with experience in developing and optimising data science products as we seek to improve the personalisation capabilities and their performance for our OSP platform.

Role & Responsibilities:

As a Data Scientist you will work closely with the team lead, management, other data scientists and software engineering teams to identify, scope, plan and manage projects, and effectively communicate complex technical issues and findings to a range of technical and non-technical internal audiences.

You will work on projects in all the areas touched by data science, dealing with complex problems and having a real impact on the operational performance of the company. You will be given autonomy in how you approach these problems and will be encouraged to research and seek out innovative solutions.

Communication is key; you will be in constant contact with business stakeholders and will need to work with developers both within the team and in other technology teams to ensure that your solutions are properly productionised and can be supported.

You may be asked to perform tasks as required by management deemed as a reasonable request. This job description is a summary of the typical functions of the role, not an exhaustive or comprehensive list of possible role responsibilities, tasks and duties and is subject to review. The responsibilities, tasks and duties of the job holder might differ from those outlined in the job description and other duties, as assigned, might form part of the job.

Knowledge, Skills and Experience

  • Degree in Mathematics, Statistics, or other quantitative sciences.
  • Experience building productionised machine learning models at scale with a preference for MVP and iteration.
  • Demonstrated computer programming ability including fluency in two or more of Python, Java (or equivalent), and SQL.
  • Experience conducting research and analysis on large data sets and providing rigorous interpretations of the results.
  • The ability to model complex problems mathematically and/or computationally
  • A solid understanding of key statistical concepts.


  • Portfolio of past work (applications, analysis, visualisations, blog posts, presentations etc.)
  • Successfully conducted research of significant scope – a Master degree or Ph.D. will be looked on favourably.
  • Experience working on recommendation systems
  • Experience with Google Cloud Platform.
  • Knowledge of common machine learning toolkits (e.g. Scikit-Learn).
  • Knowledge of deep learning frameworks (e.g. TensorFlow, Theano, Torch..).


  • Craftsmanship – demonstrates breadth and depth of knowledge and skill; upholds quality and continuous improvement; can adapt the ideas of others; displays high levels of initiative.
  • Trust – demonstrates high levels of trust between individuals and teams; espouses respect, openness, honesty and knowledge sharing.
  • Collaboration – works well with others and actively contributes towards team/department/division objectives to enable high performance of own and fellow teams; displays the generosity to help others succeed at own expense.
  • Autonomy – accepts ownership of what they do; relishes empowerment to drive innovation; takes accountability and responsibility for their own actions.
  • Learn Fast – ability to learn fast through experimentation; understands that failing is acceptable; recognises the importance of learning from failure quickly, without attributing blame.
  • Leadership – proven ability to inspire, motivate and empower others; able to make tough decisions and handle difficult situations and face major challenges with positivity, confidence and pragmatism; adept communicator.

What we can offer you

A relaxed, international, talented, creative and friendly environment, where we invest in our employees, ensuring we provide them with the best in-house and external training programs available.

  • Flexible working hours with short Fridays
  • Reduced hours in August
  • Private Health Insurance
  • Life Insurance
  • Ticket Restaurant
  • Ticket Transport
  • Ticket Kindergarten
  • Flexible WFH policy
  • Share-saving scheme
  • Gym membership discounts
  • Fresh fruit, snacks, tea and coffee
  • Monthly social events
  • Table football, board games and Nintendo Switch
  • Tech Talks and internal trainings
  • English, Spanish and Catalan language courses

We are growing rapidly, making it a very exciting time to join, as we are currently at a brand new office in the 22@ district - the thrilling tech area of Barcelona.

Anything else?
There’s a lot going on at Ocado Technology! Click to find out more about Ocado Technology and our recruitment process.

Ocado is an equal opportunities employer and as such makes every effort to ensure that all potential employees are treated fairly and equally, regardless of their sex, sexual orientation, marital status, race, colour, nationality, ethnic or national origin, religion, age, disability or union membership status.

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