Richemont Data Science Intern

Employment
Internship
Seniority
Intern
Posted
Jul 14, 2026

About Richemont

Richemont is one of the world’s foremost luxury groups, stewarding a distinguished portfolio of maisons across jewellery, watchmaking, fashion and accessories, including Cartier, Van Cleef & Arpels, Jaeger-LeCoultre and Montblanc. As an employer, it combines the heritage of artisanal excellence with a forward-looking culture shaped by innovation, client-centricity and responsible business. Its global teams operate in an environment that values craftsmanship, entrepreneurship and collaboration, offering opportunities to grow within iconic maisons and group functions alike. Richemont attracts professionals who aspire to contribute to enduring luxury, preserving rare savoir-faire while helping define the future of high craftsmanship.

Data Science Intern at Richemont in La Chaux-de-Fonds. Support machine learning and analytics initiatives within luxury goods.

Role & Responsibilities

  • Assist in collecting, cleaning, and processing datasets from various business units
  • Support the development and validation of machine learning models under senior data scientist supervision
  • Conduct exploratory data analysis and create data visualizations for stakeholder presentations
  • Contribute to documenting analytical methodologies and best practices
  • Participate in cross-functional projects spanning retail, e-commerce, and supply chain analytics

Qualifications

  • Currently pursuing or recently completed a degree in Data Science, Statistics, Mathematics, Computer Science, or related quantitative field
  • Demonstrated proficiency in Python or R for data manipulation and analysis
  • Familiarity with SQL for database querying
  • Understanding of fundamental machine learning concepts and statistical methods
  • Strong analytical and problem-solving capabilities

Skills

Python or R SQL Data visualization (Tableau, Power BI, or Matplotlib) Machine learning fundamentals Statistical analysis Excel Git or version control systems

Experience

No prior professional experience required; academic projects or internships demonstrating data science application are advantageous.

Education

Currently pursuing or recently completed Bachelor's degree (or equivalent) in Data Science, Statistics, Mathematics, Computer Science, Engineering, or related quantitative discipline.

Workplace

This position is based in La Chaux-de-Fonds, Neuchâtel, Switzerland.

Culture

Richemont fosters a refined, international workplace where its Maisons preserve exceptional craftsmanship while benefiting from the strength and perspective of a global luxury group. As an employer, it values long-term stewardship, collaboration, innovation, and the development of talent within an environment shaped by heritage, creativity, and high standards.

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

A.

The luxury industry is characterised by a diverse and nuanced nomenclature. Esteemed houses frequently employ proprietary terminology, and even within a single organisation like Richemont, 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 «Data Science Apprentice», «Junior Data Scientist Intern», «Analytics Intern», «Machine Learning Intern», and other variations. Our sophisticated search architecture anticipates these variations, ensuring that inquiries using related terms will seamlessly yield the exact roles you desire.

Richemont

Richemont Data Science Intern

La Chaux-de-Fonds, Switzerland

Continue to the application.