People / Students / Class of 2023
Xin (Susie) Shu graduated Summa Cum Laude from the University of Missouri in 2022, with a B.S. in Statistics and a B.A. in Journalism with the highest honor. Her passion for data analytics stemmed from a data journalism project where she analyzes the public records of racial discrimination in policing. This project allowed her to understand complex social phenomena from a quantitative angle and piqued her interest in delivering insights through data storytelling. Since then, she seized every opportunity to build a strong technical background with the aspiration of being a data scientist, to not only uncover social injustices and change the status quo but to also help stakeholders make decisions with data-driven insights. During her undergraduate study, Xin investigated Portuguese bank marketing datasets to assist stakeholders to predict term deposit subscriptions and correspondingly improved precision marketing strategies for sourcing more clients. She also worked in a data-intensive lab to classify burnt and unburnt fields using image-processing techniques to cope with wildfires and ecological issues. She applied oversampling using SMOTE to tackle data imbalance and obtain a higher AUC score by constructing a convolutional neural network. In 2021 summer, Xin interned at the music team of ByteDance as a strategic analyst for three months, responsible for optimizing Louvain clustering from a perspective of content operation. Her refined algorithm improved the efficiency of identifying promising music categories and enhanced the commercial value of high-quality but low-consumed artists. After gaining a deeper understanding of the algorithm, she took the initiative to expand the application of Louvain clustering to classify TikTok music influencers to discover those who are potential promoters of ByteDance-friendly songs. In the following summer, Xin became an intern at the go-to-market team of NVIDIA where she further witnessed the power of cutting-edge AI in business settings. She assisted the team to construct lead scoring models to prioritize high-quality leads and worked closely with the data engineer team to improve the customer analytics framework for different GTC (global AI conference) events and CRMs. Throughout her academic and professional experience, Xin honed her technical and analytics skills by leveraging data analytics tools such as Python, SQL, R, and Tableau to tackle real-world business puzzles. As a current student in the MSiA* program at Northwestern University, Xin is thrilled to further enhance her quantitative skills and transform data into assets that help companies to deliver business insights and improve business performance. She particularly looks forward to taking courses such as Data Mining, Analytics Value Chain, and Social Network Analysis. Outside of school and work, Xin enjoys dancing, traveling, and spending time with friends.
*later renamed MS in Machine Learning and Data Science
