Data analyst focused on public-domain demographic analysis — the kind of work that serves civic understanding rather than commercial metrics.
My projects center on reproducible pipelines built with open data: from raw source files through cleaning, transformation, and publication-ready outputs. I care about the full chain, not just the model or the chart at the end.
Demographic Shifts in Aruba (2015–2023) Structural analysis of workforce aging and demographic change using CBS Aruba data. Python · pandas · Jupyter · CI pipeline · Makefile.
Neighborhoods of The Hague (2016–2024) Demographic composition by migration background and gender across Den Haag wijken. R · RStudio · Quarto · open municipal data.
Languages — Python, R, SQL
Data — DuckDB, pandas
Notebooks & publishing — Jupyter, RStudio, Quarto
Shell — zsh, sed, awk
Infrastructure — CentOS Stream, Miniconda, Google Cloud SDK
Version control — Git, GitHub
Reproducibility is a first-class requirement, not an afterthought.
Public data belongs to the public — and so do the analyses built from it.
Foundational tools compound in value; I invest in learning them deeply.