Lead Data Scientist

Data & Analytics Porto, Portugal



We are looking for a person to lead a team of Data Scientists who are seeking to build the next-generation intelligent platform for online luxury fashion, powered by large scale data and state of the art Information Retrieval Systems with Machine Learning and Deep Learning 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.

  • Apply advanced Machine Learning (ML) and Learning to Rank techniques to drive business decisions;
  • Mentor new joiners and help team to meet deadlines and deliverables;
  • Work hand-in-hand with engineering in multidisciplinary teams;
  • Make sense of complex unstructured data;
  • Research and developing with senior team members novel approaches for the business;
  • Help the business define Data Science strategy and working on new ways to make the most of data span.
  • Work closely with engineering team to integrate ML algorithms into the platform;
  • Working closely with product owners in devising and assisting the product;
  • Design and develop state of the art Learning to Rank algorithms;
  • Help in the design of new features in the product, and drive innovation inside the company through the use of disruptive technologies;
  • Helping finding new talent for building the next-generation of Farfetch data scientists.
  • Preferably have a MSc or PhD in related topics such as Machine Learning, Information Retrieval, Signal Processing, Speech Processing or Optimization;
  • Have a background from fields such Computer Science, Electrical Engineering, Physics, Biomedical Engineering, Statistics, Applied Mathematics;
  • Knowledgeable in the following subjects: Learning to Rank (e.g., RankNet, ListNet), Information Retrieval and algorithm performance metrics (e.g., NDCG);
  • Have proven track record building and delivering ML products;
  • Fluent in Python and common numerical and Math & ML packages (NumPy, SciPy, scikit-learn, pandas, Keras, TensorFlow, PyTorch). R candidates are also encouraged to apply;
  • Experienced dealing with large amounts of data and building data pipelines;
  • Knowledge of big data technologies is a plus (Hadoop, Spark, Hive);
  • Non-relational databases (e.g., cassandra, Big Query) and streaming platforms know-how (e.g., kafka) is a plus;
  • Strong English skills, both written and spoken;
  • Scientific and technical publications are possible and encouraged;
  • Applicant should be interested to keep up to date with scientific advancements.