Data Scientist - Search And Recommendations

Detalhes da Vaga

FARFETCH exists for the love of fashion. Our mission is to be the global platform for luxury fashion, connecting creators, curators and consumers.
We're a positive platform for good, bringing together an incredible creative community made up by our people, our partners and our customers. This community is at the heart of our business success. We welcome differences, empower individuality and celebrate diverse skills and perspectives, creating an inclusive environment for everyone. We are FARFETCH for All.
TECHNOLOGY We're on a mission to build the technology that powers the global platform for luxury fashion. We operate a modular end-to-end technology platform purpose-built to connect the luxury fashion ecosystem worldwide, addressing complex challenges and enjoying it. We're empowered to break traditions and revolutionise, with the freedom and autonomy to make a difference for our customers all over the world.
PORTO Our Porto office is located in Portugal's vibrant second city, known for its history and its creative yet cosy environment. 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 We are seeking a highly motivated Data Scientist to join our team in building an advanced personalization platform for online services, leveraging large-scale data and state-of-the-art Machine Learning techniques. You will work within a dynamic, interdisciplinary team comprising software engineers, data scientists, and machine learning engineers, reporting directly to the engineering leadership. Your role will focus on search, recommendations, and hyper-personalization, with a strong emphasis on information retrieval and recommendation systems. The platform serves millions of requests daily, powered by Python microservices and processes billions of data points to hyper-personalize the customer experience.
WHAT YOU'LL DO 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.Work on developing scalable solutions that can handle millions of requests daily, ensuring high performance and reliability.Stay updated with scientific advancements and contribute to scientific and technical publications when possible.WHO YOU ARE 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.
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Salário Nominal: A acordar

Fonte: Jobleads

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