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

Beschreibung:

Our team at the BMW Group focuses on global residual value risk management at BMW Financial Services. We are dedicated data scientists who support strategic decisions for the future value of our premium vehicles.

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 to integrate agentic AI into our daily processes.

* In addition, you analyze data sets from various markets to derive measures and recommendations for the future.

* Moreover, you contribute to the creation of new analysis tools to increase our market insights.

* Additionally, you will have the opportunity to learn from and contribute to discussions that shape our global vehicle evaluation.

What should you bring along?

* Studies in computer science, data science, statistics, mathematics, economics or a similar field.

* Profound skills in two of the following: Python, R, or SQL with experience in supervised learning algorithms.

* Good grasp of statistics and its application in modeling.

* Excellent knowledge of the Microsoft Office package.

* Motivation to expand your knowledge on global electric car market development.

* Analytical thinking and structured mindset.

* Excellent English skills in oral and written form; German is a plus.

Would you like to support our team in shaping the future of vehicle value with data-driven insights? 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 07/01/2026

Duration: 6 months

Working hours: Full-time

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

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. Learn more here