About Me

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I am a Ph.D. candidate in Statistics at Harvard University, where I am advised by Kosuke Imai. My research centers on Causal Inference in the context of policy evaluation and learning, with emphasis on statistical and algorithmic decision-making. My goal is to extract statistically reliable information from data to help decision makers make better choices.

In the summer of 2025, I was a research intern in the Experimentation & Causal Inference group at Netflix.

Before joining Harvard, I earned degrees from the University of Oxford (MSc in Statistical Science), ETH Zurich (MSc in Applied Mathematics), and the University of Vienna (BSc in Mathematics). I also worked full-time as a Data Scientist at QuantCo, a consulting firm specializing in Statistical Machine Learning. Prior to my academic journey, I served in the Austrian Armed Forces, where I underwent training to become an army officer.

Research

For an always up-to-date list of publications, see my Google Scholar page.

Publications

Working Papers

News

  • September 04, 2025. Talk: Harvard Statistics Department, “Statistical Decision Theory with Counterfactual Loss”
  • June 02, 2025. Career: Netflix internship start
  • May 15, 2025. Talk: ACIC, Detroit, Session Talk, “Statistical Decision Theory with Counterfactual Loss”
  • May 13, 2025. Paper: Statistical Decision Theory with Counterfactual Loss is now available on arXiv

Teaching

Harvard University

  • STAT 210: Probability I (Fall 2024)
  • STAT 234: Sequential Decision Making (Spring 2025)
  • STAT 286: Causal Inference with Applications (Fall 2025)

ETH Zurich

  • Probability Theory and Statistics (Spring 2021)

Contact

Email: benedikt_koch@g.harvard.edu

LinkedIn | Google Scholar | GitHub