Data Scientist – Recommendations and Personalisation

Website Farfetch

Farfetch is building the next-generation intelligent platform for online luxury fashion, powered by large-scale data and state of the art Machine Learning, Deep Learning and Computer Vision algorithms. You will join a talented team of Data Scientists and Engineers to help build and optimize, through research and experimentation, our personalisation products. Your main goal is to enable the use of personalisation for every service across the Farfetch platform, as an example you will participate in the development of personalised recommendations, rankings and search results.



  • Design and develop state of the art algorithms, mainly using collaborative and personalisation techniques;
  • Conduct practical research with a scientific mindset, and a focus on delivery;
  • Work closely with the engineering team to integrate ML algorithms into the platform;
  • Engage with business stakeholders, product managers and designers to help identify challenges and opportunities, deriving valuable insights and deliver a shared vision of a luxury fashion personalisation;
  • Scientific and technical publications are possible and encouraged.



  • MSc or PhD in a quantitative discipline: Machine Learning, Computer Science, Statistics, Applied Mathematics, Physics or related areas.
  • Practical contact with large-scale recommender systems or other personalisation systems in production is a plus.
  • Experienced in online testing methodologies (AB Testing, Multi-armed bandits). Experienced in designing and analysing online experiments is highly valued.
  • Fluent in Python and common numerical and ML packages (NumPy, SciPy, Scikit-Learn, Pandas, Keras, TensorFlow, PyTorch, PySpark). Experience developing production software is a plus.
  • Experienced dealing with large amounts of data and knowledge of big data technologies is a plus (DataBricks, Spark, Presto, Hadoop).
  • Able to communicate findings and data science concepts clearly to both technical and non-technical audiences.
  • Fluent in English, both written and spoken.
  • Interested in keeping up to date with scientific advancements.


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