Data-driven decision making has become an integral part of corporate culture. On the job market, the demand for employees who are trained in the collection, cleaning, evaluation and interpretation of data is increasing. At the same time, there is increasing differentiation in specialisations. „Data science“, the best-known buzzword, is now only one of many different job profiles that require different skills and competences. The field of „Data X“ is highly interesting for postdocs who want to enter the non-university job market and are trained to work with data sets. Postdocs from very different empirical disciplines can enter the field – for example, from linguistics, psychology, the social sciences, neuroscience, marine research and many more. However, many postdocs are unclear about what is behind terms like data scientist, data engineer or business intelligence. What does a data scientist do on the job? What qualifications should an analytics engineer have? And how do they enter the job market? Although data experts are in demand, it is challenging to get started: most companies have multi-stage recruitment processes in which specific skills are tested.