Xin (Selina) Zhuang
About Xin (Selina) Zhuang
Xin (Selina) Zhuang is a Data Scientist with experience in natural language processing and deep learning. She has worked at ProCogia since 2020 and previously held positions at The Johns Hopkins University and NetEase.
Current Role at ProCogia
Xin (Selina) Zhuang currently serves as a Data Scientist at ProCogia, a position she has held since 2020. Her role involves applying her expertise in data analysis and machine learning to various projects. She has worked on a notable project for T-Mobile, utilizing her skills to derive insights and solutions that meet the client's needs. ProCogia is known for its focus on data-driven decision-making, and Zhuang's contributions align with the company's mission.
Previous Experience at The Johns Hopkins University
Zhuang has previous experience at The Johns Hopkins University, where she worked on a Natural Language Processing (NLP) project for two months in 2018. Additionally, she engaged in research related to Deep Learning and the Traveling Salesman Problem (TSP) for three months in 2019. Her time at this prestigious institution provided her with valuable experience in advanced data science techniques.
Internship at NetEase
In 2019, Zhuang completed a three-month internship as a Data Scientist at NetEase in Beijing, China. This role allowed her to apply her academic knowledge in a practical setting, gaining hands-on experience in data analysis and machine learning within a leading technology company.
Educational Background
Zhuang holds a Bachelor of Arts degree in Math and Economics, Computer Science from New York University, where she studied from 2014 to 2018. She furthered her education at the Johns Hopkins Whiting School of Engineering from 2018 to 2019, focusing on data science. Her academic background provides her with a strong foundation in quantitative analysis and computational techniques.
Technical Skills and Expertise
Zhuang possesses expertise in several technical areas, including Spark, Tableau, Python, and SQL. She has a strong foundation in Big Data, which complements her skills in Machine Learning and Natural Language Processing (NLP). These technical skills enable her to effectively analyze complex datasets and develop data-driven solutions.