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Data Scientist – Experimentation Platform

Farfetch

PortoPosted 11 days agoDirect from company

  • LocationPorto
  • Work typeHybrid
  • EmploymentFull-time
  • Posted16 October 2026
  • SourceFarfetch's careers page (Lever)
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About the role

Farfetch is a leading global marketplace for the luxury fashion industry, connecting customers in over 190 countries with items from more than 50 countries and over 1,400 of the world’s best brands and charming boutiques from around the world. Farfetch opens a world of luxury for endless expressions of style, delivering a truly unique shopping experience and access to the most extensive selection of luxury on a global marketplace.

TECHNOLOGY

The Technology team builds end-to-end products and solutions that power our marketplace, delivering an incredible experience for customers globally. From understanding customer and partner needs to designing and testing innovative hypotheses, we create industry-leading experiences for luxury customers everywhere.

PORTO

Our office is near Porto, in the north of Portugal, and is located in a vibrant business hub. It offers a dynamic and welcoming environment where our employees can connect and network with a large community of tech professionals.

THE ROLE

We are looking for an experienced and hands-on Data Scientist to join our Data team at FARFETCH, with a focus on evolving our in-house Experimentation Platform and its custom-built Statistical Engine.

Our Experimentation Platform enables teams across FARFETCH to run A/B tests, measure the impact of product changes, and make data-driven decisions at scale. At its core, our Python-based Statistical Engine processes experiment results and powers automated, self-service analytics.

In this role, you will take technical ownership of the Statistical Engine, combining strong statistical expertise with software engineering skills to improve its reliability, scalability, and analytical capabilities.

You will work closely with Data Engineering, Data Analytics, Product, and Engineering teams to modernise our experimentation capabilities, introduce advanced statistical methods, and explore how AI can accelerate platform development and improve experimentation workflows.

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