Kering Data Scientist Performance Intern
Kering is a global luxury group with a rich heritage rooted in family and entrepreneurial spirit. The conglomerate encompasses a portfolio of esteemed brands renowned for their creativity in couture, ready-to-wear, leather goods, jewelry, eyewear, and beauty, including Gucci, Saint Laurent, Bottega Veneta, Balenciaga, Alexander McQueen, Brioni, Boucheron, Pomellato, Dodo, Qeelin, Ginori 1735, as well as Kering Eyewear and Kering Beauté. Guided by their history and heritage, Kering's Houses design and craft exceptional products and experiences that reflect the Group's commitment to excellence, sustainability, and culture. This vision is embodied in the Group's signature: Creativity is our Legacy. With 47,000 employees, Kering achieved a revenue of 17.2 billion euros in 2024.
- Industrialize anomaly detection tools.
- Analyze large-scale data to detect and predict equipment anomalies in real-time.
- Propose new algorithms to enhance existing systems.
- Demonstrate interest and capability in real-time data processing.
- Proactive and independent work style.
- Willingness to work collaboratively in a team environment.
- Passion for continuous improvement and agile methodologies.
- Familiarity with recent technologies such as Kafka, Spark, HDFS, S3, Minio, Alloy, Jupyter.
- Proficiency in English.
- Strong analytical and problem-solving skills.
- Ability to work with large datasets and real-time data processing.
- Knowledge of machine learning and artificial intelligence.
No prior professional experience required, but familiarity with relevant technologies and methodologies is expected.
Currently enrolled in a relevant degree program.
Continuous mentorship and guidance from experienced colleagues.
Kering is committed to diversity in all its forms—gender, age, nationality, culture, religious beliefs, and sexual orientation—enriching the workplace and enhancing adaptability in a changing world. As an equal opportunity employer, Kering welcomes applications from all qualified candidates, regardless of background.

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