Even though I’m a political scientist by education, I’ve always been fascinated by statistics, machine learning and computer science.
Currently I’m building predicive models for property valuation. I found myself not only intrigued by the analytical part of the project, but the implementation as well. Thus, lately I’ve been working on implementing these predicitve models in application software. Although R certainly has it’s strength as an analytical tool, I’ve found myself enjoying having to write production code in the R language as well.
Since I was originally merely an analyst, I do not detest the R language like most other developers.
Master of political science from Aarhus University in 2015 with thesis: Corruption and national cohesion (grade: 12/A). grade avg.: 11.7 (top 2 %)
Head of Section – Danish Ministry of Taxation (2015 – now): In my current position, I work as a statistician/data scientist/R-developer. I work with predictive models and their integration in application software. My primary focus is writing optimized, production-ready R-code and deployment.
I taught quantitative methods/statistics as a student teacher in 2014 (Political Science – Aarhus University).
As a part of my education and later as a part-time job, I worked as a junior consultant at the research company Epinion Aps (2013-2014). I mainly handled their advanced analytics and big data projects, as well as automation of various procedures.
During my studies I worked on-off as a research assistant (march 2012 – december 2014), helping a professor do research on macro-level electoral behavior.
- R (experienced)
- Python (proficient)
- stata, SPSS, SAS/SQL (proficient)
- GIT (source control)
- Analytics, Data management, Data Science, Research, Scrum, statistics
- Danish, English