Master's Internship in Supply Chain Engineering, Data Science, and Industrial Logistics at L'Oréal, Paris L'Oréal Groupe in France

L'Oréal Groupe is offering a six-month paid internship for Master 1/2 students specializing in Supply Chain Engineering, Industrial Engineering, Logistics, Statistics, or Data Science. The position is based in Paris, France, with opportunities at various industrial sites across the country. The internship focuses on the analysis and optimization of supply chain processes, participation in innovation and digitalization projects, operational data analysis, performance dashboard development, and scenario modeling and simulation to support decision-making. Interns will collaborate with cross-functional teams including S&OP, factories, purchasing, and logistics.

Applicants must be enrolled in a relevant Master's program (Bac+4/5) and fluent in both French and English. Advanced Excel skills are required, and familiarity with SQL, Power BI, Tableau, or programming languages such as Python/R is advantageous. Experience with WMS/TMS or ERP (SAP) is a plus. The ideal candidate will have strong analytical and problem-solving skills, be rigorous, results-oriented, proactive, curious about innovation, and able to work effectively in teams within an international environment.

The internship provides a gross monthly stipend of EUR 1,700, transportation cost participation, one day of paid leave per month, access to L'Oréal Learning Platform, staff sales at preferential rates, flash sales for friends and family, and, depending on the site, access to a gym. The application deadline is January 5, 2026, with the internship starting in July 2026. The recruitment process includes a 30-minute recruiter interview and a 45-minute meeting with the potential future manager.

To apply, candidates should submit their application via the L'Oréal Careers portal, ensuring they meet all eligibility criteria. This opportunity is ideal for students seeking hands-on experience in supply chain management, industrial engineering, and data-driven process optimization within a leading global company.