Academic CV

For an exhaustive & more general overview of what I’ve done, please visit my LinkedIn profile.

Education

  • M.Sc. Data Science for Public Policy (2023 – 2025)

    Hertie School, Berlin, Germany – 1.31
    Focus Bayesian modelling, computational statistics, causal inference

    Thesis “Modelling Week-to-Week Voting Intention Change in Germany: A Bayesian Imputation Approach Using High-Frequency Panel Data” – 1.31
    Supervisors Dr. Will Lowe, Prof. Dr. Michael Mäs

  • M.P.P. Master of Public Policy (2020 – 2023)

    Hertie School, Berlin, Germany – 1.41
    Focus Policy analysis, climate & energy policy, social movements

    Thesis “A Sudden Surge in Climate Awareness: Evidence from German Political Polls in 2019” – 1.71
    Supervisor Prof. Mark Kayser, PhD

  • B.Sc. Economics (2016 – 2020)

    Heidelberg University, Germany – 1.71
    Focus Decision & game theory, neural & behavioural economics

    Thesis “Air Temperature and Mortality: An Analysis of Potential Social Impacts of Global Warming using Machine Learning” – 1.71
    Supervisor Prof. Dr. Christian Conrad

  • Courses in B.Sc. Management & Technology (2014 – 2015)

    Technische Universität München (TUM), Germany
    Focus Numerical optimisation, statistical programming

    Further courses & certifications
    • Certificate in Advanced English (CAE, C1 level) – Cambridge Assessment English (2020)
    • Exchange semester at SGH Warsaw School of Economics, Poland (2019)
    • Exchange semester at SNSPA School of Public Administration, Bucharest, Romania (2023)
    • Extra-curricular junior courses in software development, Technische Universität Dresden (2009 – 2014)

Experience

  • Research Assistant (since 2024)

    Forschungszentrum Informatik (FZI), Karlsruhe/Berlin, Germany – House of Participation (HoP)
    Project High-frequency online panel study “Social Sentiments in Times of Crises (SOSEC)” (bi-weekly, USA/Germany, n=3500)

    Responsibilities Assurance of data quality & representativity, implementation of post-stratification and imputation methods, analysis of individual trajectories of political preference
    Supervisor Prof. Dr. Michael Mäs, Karlsruhe Institute of Technology (KIT)

  • Teaching Assistant (2018)

    Heidelberg University, Germany – Faculty of Economics and Social Sciences
    Department Chair of Econometrics & Statistics, Prof. Dr. Christian Conrad

    Responsibilities Teaching assistant for B.Sc. course “Economic & Social Statistics”, holding statistical programming lab sessions in STATA
    Supervisor Dr. Alexander Glas

  • Research Assistant (2014 – 2015)

    Technische Universität München (TUM), Germany – TUM School of Management
    Department Chair of Operations Management, Prof. Dr. Rainer Kolisch

    Responsibilities Infrastructure administration: LRZ computation cloud, VMs, network & system operations, databases
    Supervisor Dr. Christian Ruf

    Related Projects

    Please see my Projects page for an overview of my recent projects.

Technical Skills

  • Data Analysis & Statistics

    Advanced Bayesian statistics, multilevel & latent variable models, compositional data analysis, survey methodology, data simulation, data visualisation & reporting

    Intermediate Causal inference, geospatial data analysis, machine learning, text as data / NLP, larger-than-memory data handling, web crawling, synthetic data generation

    Basic Network analysis, deep neural networks, time series analysis

    Familiar Data Sets/Sources
    • German Longitudinal Election Study (GLES)
    • Social Sentiments in Times of Crises (SOSEC)
    • Forsa, Infratest dimap, Forschungsgruppe Wahlen political polls
    • ZEIT Online moving average models of polls
    • German federal- and state-level administration data
    • German and US American census data
    • Weather data nowcast & forecast (DWD)
    • OpenStreetMap (OSM)
    • Overpass Turbo
    • Berlin spatial data (FIS Broker)
    • Marktstammdatenregister (BNetzA)
    • Emissions Database for Global Atmospheric Research (EDGAR)
    • Eurostat
    • Meteostat
    • World Bank
  • Programming

    Advanced R (+ Markdown, Quarto, Shiny), STAN, SQL, Typst, LaTeX

    Intermediate Python, HTML + CSS, JavaScript, Jekyll, PHP, Bash

    Basic Julia, C++, STATA

    System & Server Operations
    • Linux (Ubuntu, Debian) setup & administration
    • Cloud computing: Positron Server, AWS S3/EC2
    • Version control: GitHub, GitLab
    • Network: Advanced configurations incl. WireGuard, VPN, SSH, DNS
    • Databases: DuckDB, PostgreSQL, MySQL, MongoDB
    • Hosting: Web servers, CMS, Nextcloud, email & domain management
    Preferred Stack
    • Windows & tunnelled Ubuntu VM
    • Positron (with remote tunnel) > VS Code > RStudio
    • R tidyverse > base R > Python
    • DuckDB > PostgreSQL
    • Typst > Quarto/RMarkdown + LaTeX > pure LaTeX
    • Mendeley > Zotero

Thanks for your interest!

Did you know I am currently looking for a PhD position? Also see my Recent Projects.

Please feel free to reach out to me or connect through LinkedIn.

  1. Grading scale: 1.0 = very good, 5.0 = fail  2 3 4 5 6