- Evidence-based decision making for social good
- Building data pipelines & infrastructures
- Machine learning applications with unstructured data
- Measurement of ‘occupation’
Malte is part of the national research data infrastructure BERD@NFDI, where he designs trainings for social scientist, who want to use unstructured (big) data such as images and text data in their analyses.
An overarching theme of Malte’s work is that he enjoys thinking about how social scientists can best leverage the promises and benefits of machine learning.
- 2019: Dr. rer. soc. (Sociology), School of Social Sciences, University of Mannheim
- 2014: Master of Science (Statistics), Department of Statistics, LMU Munich
- 2011: Bachelor of Science (Statistics), Department of Statistics, LMU Munich
- Since 03/2022: Researcher, Department of Statistics, LMU Munich
- 09/2021 – 02/2022: Visiting scholar, Machine Learning Department, Carnegie Mellon University
- 07/2014 – 08/2021: Researcher, Institute for Employment Research (IAB)
- 11/2018 – 07/2019: Analyst (on secondment), Impact Analysis Unit, German Federal Employment Agency
- 06/2014 – 12/2018: Researcher, Mannheim Centre for European Social Research, University of Mannheim