FARFETCH is hiring a
Senior Data Scientist

Summary

The job is for a Data Scientist at FARFETCH's Porto office to build an advanced personalization platform using large-scale data and state-of-the-art Machine Learning techniques. The role focuses on search, recommendations, and hyper-personalization.

Requirements

• Educational Background: MSc or PhD in relevant fields such as Machine Learning, Data Science, Information Retrieval, Computer Vision, Natural Language Processing, or related disciplines
• Strong expertise in Python and familiarity with data science and machine learning libraries such as Pandas, Scikit-learn, TensorFlow, and PyTorch
• Solid understanding of state-of-the-art machine learning algorithms, including advanced deep learning techniques, and experience with models such as transformers, BERT, and GPT
• Proficient in information retrieval techniques, learning to rank algorithms (e.g., RankNet, ListNet, LambdaMART), and relevant performance metrics (e.g., NDCG)
• Experience in developing and deploying Python microservices to handle large-scale data and requests
• Ability to conduct practical research with a scientific mindset and a focus on delivering actionable results
• Strong communication and interpersonal skills, with a proven ability to work collaboratively in a team-oriented environment
• Excellent problem-solving skills, capable of abstracting complex problems into their essential components and developing effective solutions

Responsibilities

• Design and develop state-of-the-art algorithms in domains such as ranking, natural language processing, or computer vision, with a focus on search and recommendations
• Collaborate closely with the engineering team to integrate machine learning algorithms into the platform
• Assist in the design of new product features and drive innovation within the company
• Perform experiments to demonstrate the causal impact of new ideas or implementations and conduct analyses to identify challenges and opportunities, deriving valuable insights
• Prototype, test, and productionize machine learning pipelines to enhance information retrieval and recommendation systems