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tobias-schnabel/README.md

Howdy!

I'm an MSc in Statistical Science student at Oxford passionate about causal inference, forecasting, and energy.

  • 🎓 Stats, Econometrics & Operations Research, Economics at Oxford, Maastricht (Exchange at Texas A&M), and Heidelberg
  • 🔭 Currently working on matrix completion methods for causal inference and panel data forecasting (Now available on Pip)
  • 🌱 Interested in asking and answering useful questions using data
  • 📢 Experienced in communicating technical material
  • 🚀 Future goal: Applying statistical methods to energy markets and commodity trading

Skills

  • Python: (pandas, NumPy, PyTorch, sklearn, JAX, Optuna, XGBoost)
  • R (Base, tidyverse, data.table, fect, fixest, modelsummary, ...)
  • You can find some of my projects on machine learning and data visualisation on my personal website, as well as in the GitHub highlights right below this text.

Interests

📸 Photography | 🏔️ Mountaineering | 🏎️ Formula 1

Feel free to connect and reach out, I am always working on and looking for interesting projects and inspirations!

LinkedIn

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  1. mc-forecasting mc-forecasting Public

    Work (in progress) for my Master's Dissertation in the MSc Statistical Science at the University of Oxford

    Jupyter Notebook

  2. mcnnm mcnnm Public

    Lightweight Implementation of the Matrix Completion Estimator for Panel Data presented by Athey et al. (2021)

    Python 1

  3. matrix-completion matrix-completion Public

    Bachelor Thesis in Econometrics, Maastricht University

    R 2 1

  4. sml-practical sml-practical Public

    Group project for Oxford University SB 2.2 Statistical Machine Learning

    Jupyter Notebook 1

  5. fin-ecmt fin-ecmt Public

    Problem Sets and Final Exam for Texas A&M ECMT 670: Machine Learning in Econometrics

    R

  6. Operations-Research Operations-Research Public

    Programming projects carried out with @RDHMN and @obbepulles for Maastricht University EBC2106: Operations Research

    Java