Yves Saint Laurent Data Scientist Intern
- Location
- ParisÎle-de-FranceFrance
- Employment
- Internship
- Seniority
- Intern
- Industry
- Fashion, Apparel & Leather Goods
- Posted
- Jun 19, 2026
About Yves Saint Laurent
Yves Saint Laurent stands as one of fashion’s most influential maisons, renowned for redefining modern elegance through audacity, precision, and cultural intelligence. As an employer, the House offers a dynamic environment where heritage and innovation meet, inviting talent to contribute to a legacy shaped by creativity, craftsmanship, and a distinctly Parisian spirit. Employees are encouraged to pursue excellence across design, retail, merchandising, communications, and corporate functions, within a culture that values individuality, rigor, and forward-looking vision. Joining Yves Saint Laurent means participating in the continued evolution of an iconic brand whose influence extends far beyond fashion.
Saint Laurent Data Scientist Intern, Paris. 6-month internship in machine learning and AI-driven analytics for luxury fashion.
Role & Responsibilities
- Collect and structure internal and external datasets from APIs, web sources, and open data for modeling purposes
- Perform data cleaning, transformation, and feature engineering to enhance machine learning model performance
- Conduct exploratory data analysis to identify patterns, insights, and support hypothesis-driven experimentation
- Participate in the design, training, and evaluation of machine learning models for prediction, classification, and recommendation use cases
- Prototype and explore LLM-based and agentic AI systems
- Monitor model performance and iterate on improvements based on evaluation metrics
- Build analytical datasets supporting model training and business stakeholder reporting
Qualifications
- Master's student in Data Science, Machine Learning, Computer Science, or related field
- Strong proficiency in Python and SQL
- Solid understanding of machine learning fundamentals and algorithms
- Hands-on experience with data manipulation libraries such as pandas and scikit-learn
- Demonstrated interest in AI systems, large language models, or applied machine learning
- Rigorous analytical approach and comfort working with complex datasets
Skills
Experience
Internship experience in data science, machine learning, or related analytical roles is advantageous. Candidates should demonstrate practical experience with machine learning projects, data manipulation, and statistical analysis.
Education
Currently enrolled in a Master's program in Data Science, Machine Learning, Computer Science, or a closely related discipline.
Workplace
This position is based in Paris, Île-de-France, France.
Culture
Yves Saint Laurent fosters a bold, creative, and fast-paced workplace where teams are encouraged to challenge convention while upholding the Maison’s legacy of elegance and modernity. As an employer, it values artistic vision, collaboration, and excellence, offering an environment where talent can contribute to a globally influential luxury brand with a distinctive Parisian spirit.
About Cerulean
Cerulean is the definitive career portal for the global luxury industry. We match exceptional professionals with exclusive opportunities at the world's most prestigious brands. From haute couture and fine watchmaking to prestige beauty, hospitality, and boutique retail, Cerulean centralises luxury employment to help you find the career for which you were destined.
Frequently Asked Questions
The luxury industry is characterised by a diverse and nuanced nomenclature. Esteemed houses frequently employ proprietary terminology, and even within a single organisation like Yves Saint Laurent, titles may vary across global markets to reflect local conventions. To ensure absolute clarity, Cerulean assigns a standardised, industry-coherent canonical title to every listing. However, it is worth noting that this role is functionally synonymous with «Machine Learning Intern», «AI Analyst Intern», «Data Analytics Intern», «Research Data Scientist», and other variations. Our sophisticated search architecture anticipates these variations, ensuring that inquiries using related terms will seamlessly yield the exact roles you desire.