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KERING Data Scientist
  • Python
  • SQL
  • Machine Learning
  • Database
  • Data Visualization
  • NoSQL
  • Deep Learning
Groupe Kering
Paris (75)
155 days ago


About us

A global Luxury group, Kering manages the development of a series of renowned Maisons in Fashion, Leather Goods, Jewelry and Watches: Gucci, Saint Laurent, Bottega Veneta, Balenciaga, Alexander McQueen, Brioni, Boucheron, Pomellato, Dodo, Qeelin, Ulysse Nardin, Girard-Perregaux, as well as Kering Eyewear. By placing creativity at the heart of its strategy, Kering enables its Maisons to set new limits in terms of their creative expression while crafting tomorrow's Luxury in a sustainable and responsible way. We capture these beliefs in our signature: “Empowering Imagination.” In 2019, Kering had nearly 38,000 employees and restated revenue of €15.883 billion.
Kering Digital AI, CRM & Data Governance has been created to launch data strategy, operate CRM campaigns, own data governance and provide cross-brand analysis & reporting.
The AI Factory covers a prioritized portfolio of opportunities in Marketing, Commercial & Operations and is composed of a team of top talented data scientists.
The Head of this team is currently seeking an English speaking Data Scientist to join our dynamic team based in Paris and the challenge to settle an ambitious data strategy for the Group and its Brands. The team is composed of data scientists and engineers developing with Python on an AWS environment. A large variety of projects up to implementation phase are running from marketing scoring to advanced forecasting or image recognition, thanks to available data at the group level.

Job Description

Your opportunity

You will develop ambitious data science projects with Brands and deploy them in a production environment using machine learning stacks. You will also be involved in knowledge sharing with other data scientists in the team to create robust and innovative solutions.

How you will contribute

  • You will perform statistical analyses and "deep dives" into the data to understand business problems at stake.
  • You will develop, implement, measure and take ownership of predictive models, and present and discuss solutions with our business partners.
  • You will follow research literature and test promising approaches to tackle complex business problems and you will share and discuss the findings with the entire team.
  • You will be developing unique competencies or expertise in statistics, programming and data visualization and adapt them to the specifity of the luxury industry.

Who you are

We are looking for a candidate with 1-3 years of experience as Data scientist, who has attained a Graduate or PhD degree in Machine learning, Statistics, Applied mathematics or another quantitative field. She/he should have experience or skills in the following domains:

  • Successful track record in implementing Python machine learning algorithms (Random Forests, SVM, boosting algorithms, ...)
  • Knowledge / experience with deep learning is a plus
  • Having the ability to query SQL and NoSQL databases
  • Demonstrated skills at data exploration, data quality assessment and cleansing, and using analytics for data assessment
  • Demonstrated skill in the use of applied analytics, descriptive statistics, and predictive analytics on large datasets embedded into operational processes
  • Developing production-ready code is a plus
  • Devops mindset and capabilities is a plus (ability to build algorithms, but also to administrate servers)
  • Strong written and verbal communication skills
  • Being able to work in a fast-paced multidisciplinary environment
  • Being able to work autonomously
  • English spoken and written mandatory

Why work with us

Kering is committed to building a diverse workforce. We believe diversity in all its forms – gender, age, nationality, culture, religious beliefs and sexual orientation – enriches the workplace. It opens up opportunities for people to express their talent, both individually and collectively and it helps foster our ability to adapt to a changing world. As an Equal Opportunity Employer we welcome and consider applications from all qualified candidates, regardless of their background

Job Type


Start Date



Full time



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