Julian Streyczek

Bocconi University • Economics Department

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Hello there! I’m Julian, a PhD Candidate in Economics at Bocconi University in Milan. I’m supported by the German Academic Scholarship Foundation (Studienstiftung), and I spent January through May 2025 as a Visiting Fellow at Harvard University.

I use data and statistical methods to understand how digital technologies, platforms, and institutions shape individual behavior. Most of my work starts from messy real-world data: web traffic, social media, public records, text, APIs, and scraped websites. I like turning that kind of data into clear evidence using modern methods in causal inference and machine learning, combined with careful measurement and a bit of creativity.

On this website, you’ll find an overview of my work:

  • Academic research:
    • I built a dataset on newspaper paywalls, online readership, and large-scale surveys to show how restricting access to local news affects political knowledge and electoral participation.
    • In joint work, I link data on scientists, publications, citations, co-author networks, research topics, and Twitter accounts to study how social media changes scientific production.
  • Teaching slides on machine learning in economic research: I taught an undergraduate mini-course at Bocconi on how machine learning and rich data can answer real-world policy questions, from predicting restaurant health violations with review texts to measuring poverty from satellite images.
  • The Economist’s Guide to Causal Forests: I explain the intuition and statistics behind causal forests, including how they connect machine learning with causal inference and how to implement them in R.
  • Ballotpedia state legislature scraper: I wrote an R scraper that collects and formats historical party-composition data for U.S. state legislative chambers when I couldn’t find a ready-made dataset.
  • This website: I maintain this site as a customized Jekyll/GitHub Pages project forked from the al-folio theme.

I’m currently interested in data science roles where experimentation, product analytics, and causal reasoning matter. If you’d like to get in contact, feel free to reach out.