YOOX NET-A-PORTER

Marketing Data Scientist (FTC - 1 Year)

Job description

YOOX NET-A-PORTER GROUP is the world leader in online luxury and fashion which comprises a complete luxury retail ecosystem. The Group sells directly to customers globally through its own family of multi-brand online shops NET-A-PORTER, MR PORTER, YOOX and THE OUTNET. The Group’s Online Flagship Stores Division partners with many leading luxury brands to power their own e-commerce destinations.  



The Group has 4.3 million high-spending active customers globally. As pioneers in bringing together the realms of technology and luxury, YOOX NET-A-PORTER satisfies the most discerning clientele with expertly curated products from the world’s most coveted brands, personalized end-to-end service, the latest technology, and inspiring content, all shaped by 20 years of insights into the modern shopper. 



As a global Centre of Excellence, our Digital Marketing Department is aimed to further develop our digital capabilities and create synergies across the business, as well as responsible for driving customer growth encompassing all Digital Marketing actions at the service of our stores. 

Our Digital Marketing Division are now seeking a strong, creative and analytical  Marketing Data Scientist to join the team, who will be responsible for planning, executing and managing paid campaigns.

Some of the essentials for you to know are:

Location: our offices in Milan, Italy

Reporting into: Data Science Product Manager

Contract type: Fixed Term (12-months)

Working Model: Hybrid

Here is a breakdown of what you’ll be doing:


  • As a Data Scientist at YOOX NET-A-PORTER Group you will be tackling a wide variety of data challenges including product recommendation, customer value and propensity modelling, and customer and product segmentation.
  • Work with stakeholders throughout the business to encourage a data-driven approach through the delivery of automated data products and accessible, actionable insight.
  • Identify opportunities to improve the efficiency of the Data Science team through improved work practices and the development of data assets.
  • Partner with technology teams to develop the right data, toolsets & platform to enable the benefits of the team’s work to be realised by the business.


The type of person we are looking for:


  • Bachelor’s or Master’s degree in Computer Science, Data Engineering, Statistics, or related field.
  • Good knowledge and experience of Python, Spark and SQL.
  • Strong foundation in key topics of statistics including sample selection, probability, hypothesis testing and linear regression.
  • Strong understanding of key machine learning algorithms including logistic regression, decision trees, random forests, k-means clustering.
  • Proven track record of applying machine learning algorithms to solve commercial problems.
  • A clear focus on the development of actionable insight.
  • Ability to work proactively to solve loosely defined problems.
  • Comfortable communicating with a non-technical audience.
  • Fluency both in Italian and English


From the moment you join the YOOX NET-A-PORTER GROUP we are committed to making your journey with us inspirational and evolutionary. If you are passionate, committed and thrive in a collaborative and fast-paced environment, then please apply with a CV.

YOOX NET-A-PORTER GROUP is an equal opportunities employer, we encourage people with a diverse range of backgrounds to apply. We recognize and celebrate the benefits that diversity brings to our workplace, our business and our customers. We welcome and will consider all applications regardless of race and nationality, religion, color, sex, pregnancy or related medical conditions, parental status, sexual orientation, gender identity, gender expression, age, status as an individual with a disability, or any other legally protected characteristics.

If you require any reasonable adjustments to complete your application, please do not hesitate to advise us accordingly.

Experience Level: Entry level

Workplace Type: Hybrid

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