I am data scientist and statistician in the field of anti financial crime and an ex-social science researcher studying elections and legislators with modern computational social science methods. Currently, I lead a project at the Frankfurt-based AI startup spotixx on fair and explainable machine learning models for the financial service industry. Together with Paul C. Bauer and Denis Cohen, I am writing a book on Applied Causal Analysis with R (under contract with Chapman & Hall/CRC Press), in which we connect traditional causal estimation approaches with cutting-edge methods from causal machine learning. I am also an active content creator on LinkedIn where I regularly blog and post about topics around fairness in machine learning, explainable AI and the intersection between statistics and data science.

Formerly, I have been working as a data science consultant at a large German bank dealing with machine learning pipelines for anti money laundering transaction monitoring. I hold a M.Sc. degree in Methodology and Statistics from the University of Utrecht (NL) and a Dr.rer.soc. on Statistical Detection of Systematic Election Irregularities from the University of Mannheim.

My article “Bayesian Nested Analysis” with Ingo Rohlfing got accepted for publication in “Sociological Methods and Resarch”. In the article, we show how Bayesian statistical methods can aid multi-method research in the social sciences.

The career portal for graduates from mathematics, IT, science and technology (MINT) “Hi:Tech Campus” has published an interview with me about my role as a data science consultant in anti financial crime (in German).

I taught the workshop “AI in Anti Financial Crime” at Sopra Steria’s Graduate Program of Risk, Finance & Compliance in Hamburg. The workshop introduced a group of FinCrime professionals to the landscape of different AI approaches, discussed their possibility to tackle every-day problems within Anti Financial Crime Operations, and highlighted a hands-on use case on machine learning-based customer segmentation in Transaction Monitoring.