Yves Saint Laurent Data Scientist Intern
Saint Laurent, a prestigious name in the luxury fashion industry, was established in 1961 and is renowned for pioneering the luxury ready-to-wear movement with its iconic 'Rive Gauche' line. As part of the Kering Group since 1999, Saint Laurent continues to lead the luxury sector under the creative direction of Anthony Vaccarello. The brand offers a diverse range of products including women's and men's ready-to-wear, shoes, bags, small leather goods, jewelry, scarves, ties, and eyewear.
- Ensure data consistency to secure the reliability of analyses, algorithms, and tools.
- Understand business issues and data challenges related to retail, supply, production, and pricing.
- Develop intelligent decision-making models to optimize key performance indicators such as sell-through and availability rate.
- Support operational teams in adopting data-related projects to enhance their engagement and sponsorship.
- Identify and monitor success factors of ongoing data projects using a test & learn approach.
- Master's degree in statistics or data science, seeking a final year internship.
- Proficiency in Office software, particularly Excel and PowerPoint.
- Proficiency in Python, SQL, and Google Cloud Platform (GCP).
- Strong technical skills in modeling, mathematics, applied statistics, and database manipulation.
- Familiarity with time series forecasting models.
- Good analytical skills to identify risks and opportunities.
- Fluency in English and French, both written and spoken.
No prior professional experience required, but strong technical and analytical skills are essential.
Master's degree in statistics or data science.
Opportunity to work in a leading luxury fashion house with exposure to diverse data projects and a multicultural environment.
Saint Laurent fosters a diverse and inclusive workplace, valuing gender, age, nationality, culture, religious beliefs, and sexual orientation. The brand encourages individual and collective talent expression, enhancing adaptability to a changing world.