Data Scientist - Recommendations

Farfetch (NYSE: FTCH)

  • Location
    • Porto
  • Date Posted
  • 20 Mar 2020
  • Function
  • Data Science
  • Sector
  • Retail

Farfetch exists for the love of fashion. We believe in empowering individuality. Our mission is to be the global technology platform for luxury fashion, connecting creators, curators and consumers.

Product

We’re designing impactful products and experiences that fulfil all our customer and partner needs from fashion lovers to the brands, boutiques and start-ups that operate within our platform ecosystem. Our team covers the Farfetch.com website and apps, all our B2B products and in-store experiences. We’re passionate about what we can achieve together, continuously researching, testing, launching and refining new products to push the boundaries of what’s never been done before.

Porto

Our Porto office is located in Portugal's vibrant second city, known for its history and its creative yet cosy environment. We welcome new ideas and a large number of our people. From Account Management to Technology and Product, whatever your skills are, you'll find your fit here. You can have an informal meeting in the treehouse or play the piano in your lunch break!

The role

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, Engineers and Product designers to help build and optimize, through research and experimentation, our data-driven products.

What you'll do

  • Design and develop state of the art algorithms in the area of Recommender systems;
  • Conduct practical research with a scientific mindset, and a focus on delivery;
  • Build large scale data pipelines;
  • Work closely with the engineering team to integrate ML algorithms into the platform;
  • Engage with business stakeholders, product managers and designers to help deliver a shared vision of a luxury fashion recommender system

Who you are

  • MSc or PhD in a quantitative discipline: Machine Learning, Computer Science, Statistics, Applied Mathematics, Physics or related areas.
  • Hands-on and experienced with Recommender Systems. Practical contact with large-scale recommender systems in production is a plus.
  • Knowledgeable of online testing methodologies (AB Testing, Multi-armed bandits). Experience 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). R candidates are also encouraged to apply; Experience developing production software is a bonus.
  • Experienced in dealing with large amounts of data and building data pipelines; Knowledge of big data technologies is a plus (Spark, Hive; GCP).
  • Highly fluent in English, both written and spoken.