Hybrid Data Scientist – Search, Rankings

at FARFETCH

• Job title: Data Scientist – Search, Rankings
• Job type: Full Time
• Experience level: Mid level, Senior
• Salary: Not specified
• Degree requirement: Bachelor's Degree
• Tech skills: BigQuery, ElasticSearch, Flask, Microservices, Pandas, PySpark, Python, PyTorch, Scikit-Learn, Spark, SQL, Tensorflow
• Location requirements: Hybrid, Porto, Portugal

About the role

• Data Scientist focusing on rankings for a luxury fashion marketplace. Collaborating with engineers to enhance user experience and product discovery.

Responsibilities

• Farfetch is a leading global marketplace for the luxury fashion industry. The Farfetch Marketplace connects customers in over 190 countries and territories with items from more than 50 countries and over 1,400 of the world’s best brands, boutiques, and department stores, delivering a truly unique shopping experience and access to the most extensive selection of luxury on a global marketplace.
• 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.
• TECHNOLOGY
• We're on a mission to build end-to-end products and technology that powers the an incredible e-commerce experience for luxury customers everywhere, understanding the motivations and needs of our customers and partners, to designing and testing hypotheses, to creating industry-leading experiences for luxury customers.
• THE ROLE
• We are seeking a highly motivated Data Scientist to join our Search & Rankings team within the Consumer Products domain. This team is responsible for the core discovery experience that connects millions of luxury fashion lovers with items from over 1,400 of the world’s best brands.
• You will work in a dynamic, interdisciplinary team alongside Software Engineers and Machine Learning Engineers. While our MLEs focus on building robust MLOps pipelines and scaling infrastructure, your focus will be on the "brain" of the system: deeply understanding user intent, designing complex ranking logic, and proving value through rigorous experimentation.
• One of your primary focus areas will be Rankings. Advancing our Learning to Rank (LTR) approaches for Brand, Category, and Search PLPs, which account for approximately 90% of our traffic. Additionally, you will drive the modernization of our Search Engine solutions and broader discovery initiatives as our product scales.

Requirements

• A graduate in Machine Learning, Information Retrieval, Data Science, Computer Vision, NLP, or related fields.
• Algorithm Mastery: You have a solid understanding of Learning to Rank (e.g., LambdaMART, RankNet) and Information Retrieval techniques. You should have deep expertise in the search domain, spanning traditional methods like BM25 to modern Deep Learning approaches, including Transformers architectures, Sequence Modeling, and Bi-Encoders.
• Python Stack: A strong expert in Python for Data Science (Pandas, Scikit-learn, PyTorch/TensorFlow, PySpark).
• Data Fluency: Able to query and analyze complex data. Familiar with SQL and big data stores (i.e., BigQuery, ADLS, and Spark SQL), essential for gathering your own training data.
• Engineering Awareness: Comfortable writing clean code that can be easily handed off to MLEs. Experienced in microservices (FastAPI/Flask) is a strong plus. Experienced in Elasticsearch or Solr is also a plus.
• Scientific Mindset: You rely on data and experimentation to make decisions, not just intuition.
• Adaptability: You are happy to pivot between deep Ranking problems and broader Search/Query understanding challenges as business needs shift.
• Team Player: You value collaboration over isolation and are eager to work with Engineers and Product Managers to ship real value.

Benefits

• Health insurance for the whole family, flexible working environment and well-being support and tools
• Extra days off, sabbatical program and days for you to give back for the community
• Training opportunities and free access to Udemy
• Flexible benefits program