Jurgen recently graduated with a Masters of Science Degree in Economics from California Polytechnic University. There he worked on various research and consulting projects as both a graduate research assistant and through independent study. His most recent project involved analyzing a very large dataset from the National Longitudinal Survey to estimate the effect of educational level on wages. Jurgen thoroughly enjoys all aspects of Data Science and is eager to move into a career that can help him learn and progress further in the field. Jurgen placed in the top 10% of the Higgs Boson machine learning challenge. He used ensemble learning to stack a neural networks, Xgboost, gradient boosted trees as well as Random Forest to predict housing prices in Ames, Iowa. He placed in the top 3% of all participants on Kaggle.