Overview
  /  
Meet our Students
  /  
Student Profiles
  /  
Vincent Wang

Photo of Vincent Wang

Vincent graduated with first honor award from the Hong Kong Polytechnic University with a B.Eng. in Industrial and Systems Engineering in 2017. Born in Beijing, living in Hong Kong, and studying in Pittsburgh with academic exchange experience, Vincent embraces diverse culture and speaks English, Mandarin, and Cantonese fluently. Throughout his coursework related to mathematics, operations research, computing, and management science, he envisioned the enormous potential of data science to bridge over creativity and analytical skills, and shape the future world of business.

To pursue his interest in data science and gain the business acumen, the real world is his lab. Vincent worked as a data analyst intern in Hong Kong International Airport to analyze user behaviors on the airport’s official mobile app. After exploiting the data from 5 million user event logs and related flight schedules, he managed to find relationships between flight information and user browsing behaviors, and simulated the user browsing path with tree-based modeling techniques. Furthermore, Vincent proposed two recommendation systems, based on tag recommendation and item-based collaborative filtering for accurate ad delivery.
To further his career in analytics, Vincent joined Audi Innovation Research, an innovation-focused market intelligence and analytics group in Audi China. There, he conducted extensive marketing analytics projects related with price perception and brand image study of up to US$ 1.5 million value. He constructed a statistical model (Price-Sensitivity Meter) to determine the premium corridor and conducted multivariate correlation analysis (Kruskal) to identify the drivers on brand premium. In addition, he analyzed three million sales data and assisted in conducting mapping analysis across 200+ cities in China.

Furthermore, during recent summer, Vincent led Kaggle competition project on Zillow’s home value prediction. He conducted exploratory data analysis on 2.9M housing data in LA with R, built linear regression and tree based models (decision tree, random forest, boosting decision tree) to realize accurate value prediction.
Vincent is eager to join the MSiA program at Northwestern University where he can equip with cutting edge data analytics techniques through interdisciplinary curriculum and hands on industry projects. Through collaboration with colleagues at MSiA, Vincent is thrilled to combine careful analysis and wild creativity to optimize the solutions and contribute to the real-world business with the power of data science.