If you like to examine complex data material, analyze complex investments, and want to work in a motivated team, the EOS Group is the right place for you. Our analysts get to the bottom of things. You optimize our methods and tools and constantly develop them further. You can put your analytical skills to full use by pricing non-performing loan (NPL) portfolios. No portfolio is the same and it's up to you to find the right analytical story to make us successful. Your work includes pricing projects in all countries in which EOS is active in debt purchase - as well as entries into completely new markets. In addition to Germany, these include many other countries across Europe. Your work has many different aspects: You prepare analytical forecasts, exchange your findings and forecasts with colleagues at home and abroad, pull all strings together, determine opportunities and risks and present your findings to the decision-makers yourself. You are part of the holding company and have high visibility and interaction opportunities within the group. Your forecasts are later decisive for the success of the portfolios won. We offer you an environment that brings many opportunities to develop yourself as well as your team. You have successfully completed your degree in economics or business administration with a strong numerical orientation, financial mathematics, or natural sciences Relevant professional experience in the field of investment appraisal, e.g., from an activity in an investment division, debt collection, auditing or consulting company, bank, or insurance company is mandatory. You have proven to be self-organized and being able to manage complex investment assessments. You have a sound understanding of statistical measures and the ability to present relevant information for decision-makers. You enjoy collaboration with international colleagues, speak English fluently, and excel with your high comprehension, flexibility, and interest in economic contexts. You can apply your very good MS Office (especially Excel) skills in a professional setting and already have sound experience with other tools for mathematical-statistical procedures, such as R or Python.