Wen graduated with a master’s degree with four years’ experience of psychological research and data analysis in academic projects and independent non-profit organization. At NYCDSA, Wen completed five projects, including an interactive Shiny app visualizing storm events, web scraping project of TED talks, and two machine learning projects: insurance loss prediction using GBM, xgboost, Random Forest models through R, and multi-label classification problem of bank product recommendation, using Naive Bayes Classifier, xgboost, and Random Forest models. Wen is a person with entrepreneur spirit and creativity, and hopes to join a working environment that promotes critical thinking and drives hard work.
