2026 Richemont Winter Internship- Richemont Data Analyst Intern

Job description

About Richemont: 
Richemont is a leading global luxury group, home to some of the world's most prestigious Maisons in jewelry, watches, fashion, and accessories. With a rich heritage and a commitment to craftsmanship and innovation, Richemont offers a unique and rewarding environment for talented individuals seeking to build a career in the luxury industry. Richemont Taiwan plays a crucial role in the group's success in the dynamic Taiwanese market. 

 

Richemont 2026 Winter Internship Program Overview: 
It's a comprehensive three-month program designed to connect with and develop our future talent pipeline. This program offers students invaluable insights into Richemont's operations with accountable mentor, the luxury goods industry, and a chance to develop key business skills while building a strong professional network.

Internship Period: January 5th, 2026 – March 30th, 2026 
- Work Schedule: 
During Winter Break: 5 days per week 
During Semester: at least 3 days per week

 

Responsibilities:
- Data Product Localisation: Assist in customising and adapting regional data products for the local market according to the requirements of the local Maison.  
- Local Data Analysis: Perform analysis on market trends, and business performance to uncover actionable insights for local Maisons.  
- Data Solutions: Support the implementation of data-driven solutions tailored to the needs of local business stakeholders.  
- Collaboration: Work closely with regional teams, to ensure consistency and relevance of localised solutions.  

 

Requirements:

- Educational background in Analytics, Data Science, Business, IT, or related fields
- Strong analytical and problem-solving skills.  
- Good communication skills with the ability to explain complex ideas in a simple way.  
- Fluency in spoken and written English
- A passion for data, AI, and innovation  
- Strong team player with a collaborative mindset.  
- Proficiency in data tools such as Python, SQL, GCP or BI (e.g., Looker) is a plus.