5 beste Stellen als student machine learning in bayern – aktuell auf Personalsuche

Intern Data Scientist Residual Value Risk Management (f/m/x)
BMW —München
- Vollzeit
- Informatik
- Microsoft Office
- Machine Learning
- Flexible Arbeitszeiten
Thesis Quantum Computing and Generative Models (f/m/x)
BMW —München
- Vollzeit
- Informatik
- Machine Learning
- Python
- Flexible Arbeitszeiten
(Intern) Entrepreneur in Residence
Tacto —München
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- Produktion
- Künstliche Intelligenz
Bachelor- oder masterarbeit (m/w/d)
ATRIVIO GmbH —Kempten (Allgäu)
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- JavaScript
- Kostenloser Parkplatz
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19 Std.
Junior AI Engineer (m/f/d)
Artefact —München
- Vollzeit
- Azure
- Informatik
- Master
- Flexible Arbeitszeiten
1 Std.

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Intern Data Scientist Residual Value Risk Management (f/m/x)

BMW -
München

Jetzt bewerben

Details zur Stelle

Vollzeit

Leistungen

Flexible Arbeitszeiten

Qualifikationen

Informatik
R
Microsoft Office
Machine Learning
Python

Vollständige Stellenbeschreibung

THE BEST INTERNSHIP IN THEORY - AND IN PRACTICE.

SHARE YOUR PASSION.

World-leading technologies don’t make it into a BMW until they’ve undergone one of the most challenging journeys imaginable. It takes dynamic teams with outstanding technical skills to take them from the drawing board to the road. That’s why our experts will treat you as part of the team from day one, encourage you to bring your own ideas to the table – and give you the opportunity to really show what you can do.

We at the BMW Group offer you the opportunity to become part of our global residual value risk team at BMW Financial Services. This highly strategic risk area arises when vehicles leave production and begin their journey as leased vehicles. You will collaborate with a team of young and dedicated data scientists who tackle this challenge using cutting-edge analytical methods.

What awaits you?

You will support applying machine learning models to predict future prices of our vehicles on the used-car market.
Furthermore, you help integrate agentic AI into our daily processes.
In addition, you assist in analyzing data sets from different markets to derive measures and recommendations.
Moreover, you contribute to creating new analysis tools to increase our insight into the car market.
You will also gain unique opportunities to learn from and contribute to discussions on how we evaluate our premium vehicles globally.

What should you bring along?

Studies in computer science, data science, statistics, mathematics, economics or a related field.
Profound skills in two of the following: Python, R and SQL with experience in creating supervised learning algorithms.
Good understanding of statistics and its application in modeling.
Excellent knowledge of the Microsoft Office package.
Intrinsic motivation to continuously expand your knowledge on global electric car market development.
Proven analytical thinking.
Excellent command of English in oral and written form; German skills are a plus.

Do you enjoy working in an international team on strategic challenges? Then apply now!

What do we offer?

Comprehensive mentoring & onboarding.
Personal & professional development.
Flexible working hours.
Mobile work.
Attractive & fair compensation.
Apartments for students (subject to availability & only at the Munich location).
And much more, see bmw.jobs/whatweoffer

Start date: Earliest start date 01.08.2026

Duration: 6 months

Working hours: Full-time

You can find helpful tips on your application and the application process.

At the BMW Group, we place great importance on equal treatment and equal opportunities. Our recruiting decisions are based on the personality, experience, and skills of the applicants.

Legal Entity:

BMW AG

Location:

Munich

Job Field:

Market Risk

Job Id:

188504

Publication Date:

02.06.2026

Jetzt bewerben

Erweiterte Suche

student machine learning Jobs in bayern

Intern Data Scientist Residual Value Risk Management (f/m/x)

Thesis Quantum Computing and Generative Models (f/m/x)

(Intern) Entrepreneur in Residence

Bachelor- oder masterarbeit (m/w/d)

Junior AI Engineer (m/f/d)

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