Cindy Xie
About Cindy Xie
Cindy Xie is a Graduate Research Assistant at NYU Langone Health, with a background in data science and experience in various research and data analysis roles.
Graduate Research Assistant at NYU Langone Health
Cindy Xie currently holds the position of Graduate Research Assistant at NYU Langone Health. She has been contributing to the institution since 2024 in a hybrid capacity, combining both on-site and remote work in New York, United States. Her role involves conducting extensive research, likely focusing on areas pertinent to her background in data science and machine learning.
Previous Experience at HungryPanda and NYU Shanghai
Before her current role, Cindy Xie worked at HungryPanda, a Chinese food online delivery platform, where she served as a Data Scientist Intern for three months in 2022. This on-site position took place in New York, United States. Additionally, she has experience as a Research Assistant at NYU Shanghai from 2022 to 2023, as well as holding the position of Resident Assistant at NYU Shanghai in 2021 for four months.
Data Analyst Intern at Shenwan Hongyuan Securities
In 2020, Cindy Xie undertook the role of Data Analyst Intern at Shenwan Hongyuan Securities Co., Ltd., located in Beijing, China. This four-month on-site internship allowed her to gain significant experience in data analysis within the financial sector. Her responsibilities likely included data modeling, statistical analysis, and reporting on financial data.
Educational Background in Data Science
Cindy Xie has a comprehensive educational background in Data Science. She achieved a Bachelor of Science (BS) degree from NYU Shanghai, studying from 2019 to 2023. Additionally, she participated in an exchange program at New York University Abu Dhabi in 2021 for four months. She also earned a Master of Science (MS) degree in Data Science from New York University, studying from 2023 to 2025.
Expertise in Machine Learning and Data Visualization
Cindy Xie is actively engaged in exploring advanced machine learning algorithms. She emphasizes data visualization techniques to effectively communicate insights to non-technical audiences. Her blend of technical and communication skills makes her adept at conveying complex data-driven insights in a clear and understandable manner.