Thesis on the topic of unsupervised learning at Service24h from April 2026

UNS At Daimler Truck, we are changing the transport system of today and jointly achieve real effect. We take responsibility worldwide and work together as a global team. We are driving our progress and success together – each: at Daimler Truck makes the difference. Together we want to reduce our carbon footprint, increase safety on and off the road, develop smarter technologies and attractive financial solutions. All this is essential to achieve our goal – for all those who move the world. Become part of our global team: You make the difference – YOU MAKE US Customer Services & Parts is responsible for the global service and parts business for Mercedes-Benz Trucks. Within the area, our department is responsible for the International Pannendienst “Service24H” and provides quick help in numerous countries with clearly defined processes and the control of external service providers. Within the department, the Planning and Analytics team is responsible for defining, collecting and analyzing all relevant key figures used in the end-to-end process. You serve as an important influence for the daily business of the department in the management of the service providers: inside and out markets, the quality of after-sales services and customer support: inside and the strategic orientation of the department and after-sales services. As part of this thesis, the efficiency of the dispatch process is to be analyzed. The Dispatch Process is a sub-process of the Service24h, which includes the case intake by a telephone agent, the examination of necessary payment guarantees and the assignment to a nearby workshop. The aim of the final work is to identify the causes and responsibilities for over-average processing times by means of modern unsupervised learning approaches (in particular clustering and dimensionality reduction). In particular, the focus is on so-called “long-runners”, i.e. cases in which the time span between case-taking and dispatch lies clearly above the average. To this end, the existing data base is to be processed in a structured manner and optimized with respect to relevant features. Various algorithms of Unsupervised Learning are tested and the results are evaluated using defined metrics and compared to manual analysis methods and existing models. The work includes the continuous improvement of the feature engineering strategy. In addition, the results are considered critical in terms of their practical benefits for service optimization.

THE WORK Analysis, pre-processing and optimization of case and process data from CRM systems Development and implementation of methods of unsupervised learning for pattern and cluster recognition Systematic evaluation of different feature sets and algorithms Comparison and evaluation of results against manual analyses and existing (supervised) machine learning models Documentation of the procedure, results and action recommendations Presentation of insights before internal stakeholders and, if necessary, Support in deriving improvement measures

WE BEEDS An exciting and varied activity in a dynamic environment The opportunity to participate independently in projects and introduce your ideas An attractive remuneration and flexible working hours Insights into the working world of a leading company in the commercial vehicle industry Participation and participation in exciting exchange and network formats of the multi-site student @ Daimler Truck Network

THE BRINGS You are in an ongoing study in the field of Computer Science, Data Science, Data Analytics, Mathematics, Business Informatics, Engineering or Similar You have a safe handling of Python, Databricks and common machine learning and data science libraries (e.g. scikit-learn, pandas, NumPy) You have knowledge of machine learning Very good knowledge of German and English Ideally, you have experience in data processing, analysis and feature engineering You have a good feeling for data, processes and business relationships You have experiences in working with interdisciplinary teams You work structured, solution orientation and like to introduce your own ideas Additional information:

Of course, without formalities, we are not. Please apply online only and add a CV to your application, current enrollment certificate indicating the semester, current grade, relevant certificates, proof of the period of study and a mandatory or combination internship (max. total size of the annexes 5 MB).

Please understand that we no longer accept paper applications and there is no claim to return.

For further information on the setting criteria, see https://www.daimlertruck.com/karriere/studierende-absolvent

Members of countries outside the European Economic Area may send Please include your residence/work permit.

We are particularly pleased to receive online applications of disabled people and disabled people. If you have any questions, you can also contact sbv-zentrale-truck@daimlertruck.com to the site's severely disabled representative, who will be happy to support you in the further application process after your application.

Questions about the application process answered You are happy to receive HR Services by email: hr-service@hr.daimlertruck.com Students and graduates From theory to practice at Daimler Truck. Discover the transport industry at every stage of your academic career.

At Daimler Truck we promote diversity and stand for an inclusive corporate culture. We appreciate the individual strengths of our employees: You lead to the best team performance and thus to the success of our company. Inclusion and equal opportunities are important to us – no matter where you come from and who you are. We look forward to applications from people of all cultures and genders, parents, people with disabilities and people from the LGBTIQ+ community.