About
I am a postdoctoral research software engineer in the Bayesian Workflow Group at Aalto University, Finland, where I implement new developments in Bayesian statistics into software, primarily within the Stan ecosystem. My work spans method development, end-to-end data and modelling workflows, and open, well-tested research software in Python and R.
Previously I built greenhouse-gas concentration data pipelines at Climate Resource GmbH and completed a doctorate in computational statistics at TU Dortmund University on simulation-based expert prior elicitation (elicito).
Background
My path into research software engineering began in applied psychology. During my bachelor’s in Business Psychology I focussed on consumer and market research with first practice experiences at Ipsos GmbH and Produkt+Markt GmbH. To deepen my computational and statistical skills I followed up with a master’s in Cognitive Science with a focus on formal modelling, Bayesian methods, and their implementation in R and Python.
In academia I worked at Philipps-University Marburg and TU Dortmund University, where I completed my doctorate in computational statistics on expert prior elicitation and developed the open-source Python package elicito. I then joined Climate Resource as a research scientist and software engineer, developing data pipelines for earth system modelling groups, before moving to Aalto to work at the intersection of Bayesian methodology, research software engineering, and reproducible science.