Daimler Mobility AG (DMO) provides a comprehensive range of automotive financial services and innovative mobility solutions. The products range from leasing and financing offers to financial services for dealerships, commercial fleet management, procurement of automotive insurance solutions as well as new innovative mobility services.

We - the Risk Instruments department at the headquarters of Daimler Mobility AG (DMO) are globally responsible for the development of risk classification procedures and fraud prevention models. With these methods, we automate the credit decision processes of our national companies and thus play a key role in various digitization initiatives.
For the development of the different models, we not only use standardized, statistical estimation methods, but are also one of the leading departments within DMO AG in the development and application of AI and machine learning methods. We also operate a regional credit decision engine for the larger markets which is to be rolled out to our fleet management company Athlon as part of a two-year project. With our central role in various strategic digitization projects within DMO AG, we contribute to the realization of a digital customer experience and thus to the preparation of online sales.

We are looking for you - a team player (f/m/d) with an innovative mindset, strong customer focus and desire for new challenges!

From the beginning of your internship, you will be actively involved in the strategic development of our risk classification methods. In addition, you will be able to contribute in further improvement and evaluation of new approaches within innovative business projects. The internship length and effective integration into the subject and methods will enable you to use your newly acquired skills immediately. Subsequent to the internship, there are opportunities to apply for a practically oriented master thesis in our department.

• Working with the expert teams in the enhancement of quantitative risk classification models, e.g. advanced scoring and rating approaches using machine learning methods
  
• Data preparation, data analytics as well as subject-specific interpretation and presentation of the results
  
• Involvement in international projects implementing digital credit decision processes and solutions
  
• Evaluation of applicability of advanced machine learning methods in risk classification
  
• Data and portfolio analyses with the use of mathematical-statistical methods
  
• Getting started with the statistical software SAS and its further application as a core part of the internship
  
• Data analysis and VBA programming in MS Excel
  
• Creation of dashboards in MS Power BI
  
• Application of machine learning methods using R or Python
  
• Development of efficient data handling processes in cloud technologies (e.g. SQL scripting)
  
• Preparation of English and/or German presentations with MS PowerPoint for management meetings
  
• Participation in regular introduction and subject courses and lectures