About Me

I am a final year Ph.D. student at Martin Spindlers Chair of Statistics and Data Science at University of Hamburg. My research focusses on applying machine learning to causal effect estimation to understand relationships in the data that go beyond correlations. I work on software implementations and applications in business analytics with real-world industry data. I am contributor of the python package DoubleML. Previously, I have worked as a data scientist at Economic AI.

Research Work

I am passionate about turning complex data into real-world decisions and impact! In my research, I have demonstrated how to combine causal machine learning with high-dimensional industry data in order to enhance business efficiency and find causes relevant for business decisions. My research has been published in well established AI outlets and I was invited to talk at high-profile conferences such as PyConDE, KDD and Operations Research.

Teaching

I have 5+ years of experience in teaching undergraduate and graduate classes in mathmatics, statistics and data science.

News

• [Dec. 2025] Job market alert! I am entering the academic and non-academic job market, looking for opportunities to contribute and personally develop starting May 2026.
• [Sep. 2025] New Preprint. We derive new identification strategy for complier effects in the regression discontinuity design. Our application to data from opto-electronic semiconductor manufacturing at ams OSRAM is available on ArXiv.
• [May. 2025] New Preprint! Read more about our new scalable approach towards kernel-based conditional independence testing on ArXiv.

Publications

Contact

If you are interested in collaborating, feel free to reach out.

Address: Moorweidenstraße 18, 20148 Hamburg, Germany
Office Location: Room 0025
Email: oliver . schacht (at) uni-hamburg.de
Phone: +49 40 42838-1517