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leavanh/README.md

Hi there 👋

Welcome to my GitHub profile! I am Lea Schulz-Vanheyden, a passionate data scientist with a Masters's degree in Statistics and Data Science from LMU Munich. I have a strong interest in machine learning, deep learning, and natural language processing (NLP). With expertise in R and Python, I enjoy leveraging these tools to extract valuable insights from data.

Education

  • Masters degree in Statistics and Data Science from LMU Munich
  • Bachelors degree in Statistics from LMU Munich

Projects

  • "Vorwahlbefragung": A group project in R, involving the analysis of data from the Bavarian pre-election poll.
  • "LVS": A group project in R, where we examined the effects of environmental factors on the use of avalanche transceivers (LVS devices) in collaboration with the German Alpine Club and the Department of Geography at LMU Munich. The LVS project received the Best Practical Project award among the graduating class of 2020.
  • Bachelor thesis: "Recovering network structure through Latent Space Models": Explored the recovery of network structure using latent space models.
  • Consulting: "Impact of Open Access Status on Citation Count": Collaborative project in R and Python. We investigated whether freely accessible publications receive more citations compared to closed publications. The analysis focused on data from the Helmholtz Center, with an emphasis on causal inference.
  • Master thesis: "Enhancing Stance Prediction by Utilizing Party Manifestos": Investigated the effectiveness of incorporating information from political party manifestos to improve the accuracy of large language models in predicting party stances.

Contact Information

Feel free to reach out to me via email or connect with me on LinkedIn. I am open to exciting opportunities and collaborations in the field of data science and statistics. Let's connect and explore the possibilities together!

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