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📍
Luxembourg, Germany

2026 Data Scientist Internship , Amazon University Talent Acquisition

Internship
Technology
HR/People
November 20, 2025

Amazon

Consumer goods marketplace and technology platform
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Description

Are you a MS student interested in a 2026 internship in the field of machine learning, deep learning, generative AI, large language models and speech technology, robotics, computer vision, optimization, operations research, quantum computing, automated reasoning, or formal methods? If so, we want to hear from you!

We are looking for a customer obsessed Data Scientist Intern who can innovate in a business environment, building and deploying machine learning models to drive step-change innovation and scale it to the EU/worldwide.



Key job responsibilities

As a Data Science Intern, you will have following key job responsibilities:

• Work closely with scientists and engineers to architect and develop new algorithms to implement scientific solutions for Amazon problems.
• Work on an interdisciplinary team on customer-obsessed research
• Experience Amazon's customer-focused culture
• Create and Deliver Machine Learning projects that can be quickly applied starting locally and scaled to EU/worldwide
• Build and deploy Machine Learning models using large data-sets and cloud technology.
• Create and share with audiences of varying levels technical papers and presentations
• Define metrics and design algorithms to estimate customer satisfaction and engagement



Basic Qualifications

- Are enrolled in a Master's degree in computer science, machine learning, engineering, or related fields
- Speak, write, and read fluently in English

Preferred Qualifications

- Experience in at least one of the related science disciplines (optimization - LP, MIP, statistics, machine learning, process control, combinatorial optimization)
- Experience with data scripting languages (e.g., SQL, Python, R, or equivalent) or statistical/mathematical software (e.g., R, SAS, Matlab, or equivalent)
- Experience with big data: processing, filtering, and presenting large quantities (100K to Millions of rows) of data
- Experience implementing algorithms using both toolkits and self-developed code

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