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Education & Experience

My academic journey and professional experience

Education

MSc in Economics — graduating 2026

10/2024 – 08/2026

University of Cologne — Cologne, Germany

Current GPA: 1.0 (1.0 best, 5.0 worst) – Distinction, top 1%

  • Focus on Statistics and Political Economy
  • Relevant courses: Microeconometrics, Bayesian Econometrics, Probability Theory and Inference, Machine Learning Methods, Political Institutions, Macroeconomics
  • Currently on exchange at University of Tokyo: Data Science for Public Policy
  • Scholarship from the German Academic Scholarship Foundation, 2024–2026

MSc Exchange — Department of Economics

03/2026 – 08/2026 (current)

University of Tokyo — Tokyo, Japan

  • Classes: Data Science for Public Policy (ML methods, large-scale data pipelines), Advanced Development Microeconomics, Institutional Analysis of Japanese Economy
  • Scholarship from the German Academic Exchange Service (DAAD), 2026

MSc in Behavioural Science

09/2023 – 01/2025

London School of Economics and Political Science — London, UK

GPA 69% – High Merit (Distinction starting at 70%)

  • Focus on Causal Inference applied to Policy Analysis
  • Thesis: ”Distribution Sensitive Policy Analysis: Constructing a Prioritarian Social Welfare Function using Causal Evidence on Life Satisfaction” (65%), supervised by Dr. Christian Krekel
  • Essays: The Effect of Cash Transfers on Political Support (83%) — Quantitative Methods; Measuring Well-Being for Policy Analyses (69%) — Philosophy of Economics; A Dual-Process Model of Self-Defeating Behaviours (73%) — Fundamentals; The Influence of Fear and Anger on Risky Decision-Making (73%) — Fundamentals
  • Scholarship from the German Academic Scholarship Foundation, 2023–2024

BSc in Business Administration

09/2019 – 07/2023

University of Cologne — Cologne, Germany

GPA: 1.3 (1.0 best, 5.0 worst) – Distinction, top 5%

  • Focus on Experimental Methods
  • Thesis: ”Experimental Measurement of Provided Effort in Medical Processes by Diagnostic Indicator Tasks” (1.0), supervised by Prof. Dr. Daniel Wiesen
  • Seminar thesis: ”Incentives vs Commitment” (1.0), supervised by Prof. Dr. Daniel Wiesen
  • Scholarship from the German Academic Scholarship Foundation, 2020–2023

BSc Exchange Semester

08/2022 – 12/2022

Instituto Tecnológico Autónomo de México (ITAM) — Mexico City, Mexico

GPA 86% – Distinction

  • Classes: Communication in Spanish, Behavioral Economics
  • Scholarship from the German Academic Exchange Service (DAAD), 2022

Professional Experience

Vier Jahre als Wissenschaftlicher Mitarbeiter im Bereich Datenanalyse an der Universität zu Köln (04/2022–03/2026): Python-basierte Datenpipelines, Aufbereitung und statistische Analyse großer Befragungs- und Experimentaldatensätze, Git-Versionskontrolle und Ergebniskommunikation für wissenschaftliches und nicht-wissenschaftliches Publikum. Ergänzende Forschungstätigkeit am MPIfG Köln (08/2025–heute) und an der LSE (12/2023–03/2024).

Research Assistant in Political Economy — Data Science

08/2025 – present

Max-Planck-Institute for the Study of Societies (MPIfG) — Cologne, Germany

  • Developed and executed independent data science analysis projects: applied quasi-experimental methods and ML-adjacent statistical models in R to extract patterns from large cross-country macroeconomic datasets
  • Built reproducible data processing pipelines (R: ggplot2, dplyr, tidyverse) and produced publication-quality visualisations communicating findings to both specialist and non-specialist audiences (book manuscript)
  • Maintained full reproducibility via Git version control, systematic documentation of datasets and replication code
  • Under the supervision of Prof. Dr. Lucio Baccaro and Prof. Dr. Björn Bremer

Wissenschaftlicher Mitarbeiter — Datenanalyse (4 Jahre)

04/2022 – 03/2026

Universität zu Köln — Cologne Laboratory for Economic Research — Köln

  • Built and maintained Python-based data science toolchains (pandas, numpy, scikit-learn, matplotlib, oTree) for automated experiment execution, data collection, and analysis pipelines over 4 years
  • Managed and processed large survey datasets from a nationwide study (>5,000 respondents): end-to-end pipeline from data ingestion and cleaning to feature engineering, statistical modelling, and result visualisation
  • Independently developed analysis projects from design to presentation of results for academic audiences
  • Under the supervision of Prof. Dr. Daniel Wiesen

Tutor and Exam Grader

10/2024 – 07/2025

Department for Statistics, University of Cologne — Cologne, Germany

  • Taught weekly undergraduate seminars (~15 students per semester) in ”Inferential Statistics and Theoretical Econometrics” and ”Descriptive Statistics and Probability Theory”
  • Graded the undergraduate exams in ”Mathematics”

Occasional Research Assistant in Policy Analysis

12/2023 – 03/2024

London School of Economics and Political Science — London, UK

  • Applied quasi-experimental methods (difference-in-differences, regression discontinuity design) in Stata to estimate the causal effect of opening-hour regulations on dietary behavior in Germany
  • Assisted with dataset construction, variable coding, replication documentation, and manuscript editing
  • Under the supervision of Prof. Dr. Joan Costa-i-Font

Research Internship

10/2021 – 01/2022

Institute for Social Psychology, University of Cologne — Cologne, Germany

  • Conducted a systematic literature review of psychological interventions for increasing well-being, synthesizing evidence across clinical trials and experimental studies
  • Under the supervision of Prof. Dr. Detlef Fetchenhauer

Extra-Curricular

Co-Founder and Chair

06/2020 – 01/2024

Inspiration Cologne e.V. — Cologne, Germany

Student association at the University of Cologne

  • Designed and organized a series of ten public events at the University of Cologne, featuring speakers from politics and academia (average of 80 student participants per event)

Technical Skills

R Advanced

Data visualisation (ggplot2), panel data, Monte Carlo simulation, tidyverse

Stata Advanced

Causal inference (DiD, RDD), panel regressions, do-file documentation

Python Intermediate–Advanced

pandas, numpy, scikit-learn, matplotlib, seaborn, statsmodels; behavioral experiments (oTree); data processing pipelines

Machine Learning Intermediate

Classification, regression, clustering, cross-validation, model evaluation; scikit-learn toolchain

Git & GitHub Intermediate

Version control, reproducible research workflows, collaborative repositories

HTML & JavaScript Advanced

Web development, interactive data visualisation

Qualtrics Advanced

Survey design, experimental flows, large-scale data collection

Docker Grundkenntnisse

Containerisierung für reproduzierbare Analyseumgebungen; im Einsatz in einem eigenen Projekt

MATLAB Beginner

Numerical analysis

Work in Progress

Differences in Inequality Aversion across the General Public and Medical Professionals

Co-Authors: Prof. Dr. Joan Costa-i-Font, Prof. Dr. Daniel Wiesen, Prof. Dr. Gilberto Turati

Competition and Social Preferences – An Experiment

Co-Authors: Prof. Dr. Ching-To Albert Ma, Prof. Dr. Daniel Wiesen, Prof. Dr. Jing Li