Sephora Data Science Assistant Intern

Neuilly-sur-Seine • France

Thursday, January 29, 2026

Sephora, a leading name in the beauty industry, is renowned for its commitment to diversity, inclusion, and innovation. As part of the LVMH group since 1997, Sephora continues to redefine prestige beauty with a vast community of 56,000 employees across 35 countries. The brand offers an unparalleled range of nearly 500 brands alongside its own Sephora Collection, creating a vibrant and inclusive environment for beauty enthusiasts worldwide.

1. Develop and optimize machine learning algorithms such as RandomForest, XGBoost, and Generative AI.
2. Collaborate with business teams to ensure the adoption of machine learning models through monitoring and A/B testing.
3. Work on key focus areas including product recommendation, client scoring, activity forecasting, and generative AI.
4. Navigate and enhance the Sephora data ecosystem using tools like DSS Dataiku and Google Cloud Platform.
5. Contribute to impactful data science projects by leveraging large datasets to improve models.

1. Bachelor’s degree with a specialization in Data Science or Machine Learning.
2. Proficiency in machine learning techniques such as RandomForest, XGBoost, and LightGBM.

1. Proficiency in SQL and Python.
2. Experience with machine learning projects and participation in Kaggle challenges.
3. Knowledge of DSS Dataiku and Google Cloud Platform is advantageous.
4. Strong organizational skills and proactive approach to project management.
5. Curiosity and up-to-date knowledge of the latest machine learning methodologies.

Beginner level experience in data science or related fields.

Bachelor's degree with a specialization in Data Science/Machine Learning.

Interns will experience a supportive community that values authenticity and teamwork, with opportunities for personal development and leadership growth.

Sephora fosters a culture of authenticity and inclusivity, encouraging personal growth and leadership. The brand thrives on diversity and innovation, offering a dynamic environment where each team member's contributions are valued.