Data Scientist - Commercial - FARFETCH

PT Lisbon
09 Feb 2022
27 Jul 2022
Full Time
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.


We're a Data team that does it all: big data engineering, machine learning, and deep-dive analytics and insight. We're a diverse, global team who create Data solutions to provide an unrivalled customer experience. Whether it's churning gigabytes of ecommerce data, using AI to recommend the latest trends, or understanding our customers better than anyone else, we use data to promote FARFETCH's growth.


Our Lisbon office is located in Portugal's cosmopolitan capital. In this office, Farfetchers like to have catch ups in the ball pit or creative moments by the grand piano!


We are looking for a Data Scientist to join our effort in Machine Learning (ML) for Commercial. Our mission is to automate our planning and pricing actions on over 300,000 products sold by over 3000 brands and boutiques on the Farfetch marketplace. In particular, we are using large-scale time-series forecasting and optimisation methods to improve our supply planning strategy in an automated way. Reporting to the Data Science Manager of the Commercial Data Science team, you'll be part of a small team and be able to pick whatever technique is appropriate for the task at hand (including Deep Learning, Gradient Boosting, Graph Modelling, Recommender Systems, Reinforcement Learning). You will also keep an eye to what is happening in academia and industry to stay on top of recent developments. We work with large volumes of data with Python running on Databricks and Kubernetes in Google Cloud and Microsoft Azure.


    • Contribute to high-profile initiatives, architect and develop ML algorithms, focusing in particular on time-series forecasting;
    • Work with the engineering team to productionse and integrate machine learning (ML) algorithms into our backend or connect them to third-party tools;
    • Implement experimentation to measure the impact of our models;
    • Communicate complex solutions in a clear and understandable way to both experts and non-experts.


    • You have a degree in Machine Learning, Statistics, Mathematics, Econometrics or another quantitative discipline;
    • Experience in a Machine Learning or Data Science role with clear impact; exposure to Commercial, Operations, Forecasting or Pricing problems is a bonus;
    • Experience in Python software development (production-grade code, including code reviews, Agile development, version control) and familiar with ML/scientific packages.
    • You have experience using ML techniques in a business setting, such as neural networks, recommender systems, Bayesian modelling, graph ML. Experience with time-series modelling is a bonus.


    • 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
    • FARFETCH Equity plan


    • FARFETCH is an equal opportunities employer ensuring that all applicants are treated equally and fairly throughout our recruitment process. We are determined that no applicant experiences discrimination on the basis of sex, race, ethnicity, religion or belief, disability, age, gender identity, ancestry, sexual orientation, veteran status, marriage and civil partnership, pregnancy and maternity, or any other basis prohibited by applicable law. We continue to build our consciously inclusive culture as part of our Positively FARFETCH strategy throughout our business, partnerships and communities.

Use Machine Learning to improve our inventory through time-series forecasting and optimisation, working with Engineers and Product Managers.${description2}

Similar jobs

Similar jobs