After completing my studies in applied statistics, I now work at Statistics Austria in the methodology department. There, I develop new approaches to modernise statistical processes, with a focus on the use of artificial intelligence in official statistics. The aim is to make workflows more efficient and make meaningful use of new data sources, while complying with quality guidelines.

I work as a survey statistician at the German Institute for Economic Research (DIW Berlin), where I am responsible for sampling and weighting in the Socio-Economic Panel (SOEP). I ensure that our survey realistically reflects the population in Germany and that the sample is always sufficiently large. This data is used internationally to analyse social developments and evaluate political measures.

I work as a data scientist at the health insurance company, DAK-Gesundheit. My role involves developing and maintaining AI models to identify potential savings, increase customer loyalty and improve care for insured persons. Professionally, I deal with the question of how machine learning methods can create added value in the context of health insurance. Technically, I work on implementing these methods in Python and support their integration into IT processes.

As a data scientist at GLS Mobility, I actively support the transition to sustainable mobility. We enable easy payment at charging infrastructure for electric cars, highlight traffic-related emissions in business travel in our mobility consulting services, and show ways to reduce them effectively. I accompany the entire process in the consulting phase and am primarily responsible for the technical implementation of data collection and automated data evaluation. To this end, I develop models for determining emissions and dashboards for interactive presentation of the results.

I provide focused consulting on the special topic of remuneration and incentives/incentive systems in sales. In addition to strategic consulting, modelling the financial implications also plays a crucial role. My knowledge of statistics regularly makes the difference here. Furthermore, the understanding of programming that I developed during my studies helps me today when I advise on IT-related implementation and execution.

I am pursuing my doctorate at a statistics institute at the Charité University Hospital in Berlin. I advise doctoral students and postdocs on statistical analyses in the fields of clinical medicine and microbiology, and I am responsible for case number planning when preparing ethics applications. Some of these consultations lead to research projects that I supervise over a longer period of time. In these cases, I also create the R scripts for data analysis.

I currently work as a technical consultant for companies, advising them on how to use modern data platforms correctly and in accordance with best practices, either locally or in the cloud. My focus is on Apache Kafka, the industry standard for processing real-time data streams (‘streaming data’) – used, for example, by Netflix, OpenAI and BMW. Studying applied statistics has given me a solid understanding of data, analytical thinking and valuable insights into IT systems.

I currently work as a senior data scientist and solution designer at Vattenfall in the wind energy sector. My focus is on developing and scaling AI and machine learning solutions for predictive maintenance of wind turbines. In my role, I combine statistical thinking, software development, cloud architecture and strategic consulting to implement data-driven innovations with measurable business benefits and increase the reliability of electricity generation from onshore and offshore wind turbines.