Mandatory Internship Advanced Analytics starting from April 2026

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ABOUT US
At Daimler Truck, we change today’s transportation and create real impact together. We take responsibility around the globe and work together on making our vision become reality: Leading Sustainable Transportation. As one global team, we drive our progress and success together – everyone at Daimler Truck makes the difference. Together, we want to achieve a sustainable transportation, reduce our carbon footprint, increase safety on and off the track, develop smarter technology and attractive financial solutions. All essential, to fulfill our purpose - for all who keep the world moving.

BECOME PART OF OUR TEAM!

Our Finance Analytics team develops scalable solutions for Finance & Controlling at Daimler Trucks & Buses with the goal of enabling data-driven decisions and increasing process automation. We employ Artificial Intelligence to analyze large and complex datasets, derive forecasts for key business metrics, and quantify the impact of relevant influencing factors.

Are you passionate about data and eager to apply your skills in a real-world setting? We’re seeking a motivated intern to support our Cash-Flow Analytics project. Within this project, you’ll contribute to scale and further develop our Cash-Flow Forecasting solution to improve the forecasting quality and explainability as well as give steering impulses to our management. As an intern, you’ll collaborate closely with experienced data scientists and business experts. Whether you’re interested in machine learning, statistical analysis, or data visualization, this internship offers a unique opportunity to learn and grow.

WE OFFER YOU

• An exciting and varied role in a dynamic environment
• The opportunity to independently contribute to projects and bring in your ideas
• Attractive compensation and flexible working hours
• Insights into the working world of a leading company in the commercial vehicle industry
• Participation in and contribution to exciting exchange and networking events within the cross-location Students @ Daimler Truck network

WHAT YOU CAN EXPECT

• Extract and process data and perform analysis using Excel and Python
• Use case professionalization in Microsoft Azure (Data factory & Databricks)
• Further development of the Cash-Flow forecasting method
• Bring in your knowledge and ideas to setup suitable forecasting models both from a business and data science perspective

Qualifications

THAT’S WHY YOU ARE A MATCH

• You study (Business-) mathematics, Physics, Data Science, (Business-) informatics, Economics, Industrial Engineering and Management or comparable studies
• Programming skills: R or Python
• Experience in data wrangling techniques, statistics and basics in Machine Learning algorithms
• Strong Interest in Finance & Controlling
• Knowledge of MS-Office tools, in particular, MS Excel
• Language skills: English fluent, German basics preferable
• Commitment, teamwork and analytical thinking

You don’t bring everything with you? No problem! We look for skills but hire for attitude!

MAKEYOURMOVEand apply now – we‘re looking forward to it!

Additional information:

It doesn’t work completely without formalities. When sending your online application, please attach your CV, an individual letter and any references you may have (max. 5 MB).

Please understand that we no longer accept paper applications and that there is no right to get your documents returned.

We particularly welcome online applications from candidates with disabilities or similar impairments in direct response to this job advertisement. If you have any questions, you can contact the local disability officer once you have submitted your application form, who will gladly assist you in the onward application process: sbv-zentrale-truck@daimlertruck.com

If you have any questions regarding the application process, please contact HR Services by e-mail: hr-service@hr.daimlertruck.com

If you have any questions concerning the position, please contact Mr. Thomas Lohner at the following telephone number +49 176 309 711 53

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