Jade Wu
About Jade Wu
Jade Wu is an Applied Data Scientist II at Civis Analytics, with a background in data science and statistics. She has previously held positions at Duke University, IBM, and Georgia Institute of Technology, and earned her Bachelor of Science degree from the University of North Carolina at Chapel Hill.
Current Role at Civis Analytics
Jade Wu serves as an Applied Data Scientist II at Civis Analytics, a position held since 2021. In this role, Wu applies data science techniques to support various projects and initiatives. Civis Analytics focuses on data-driven decision-making, and Wu contributes to this mission through analytical expertise and problem-solving skills.
Previous Experience at Duke University
Prior to her current role, Jade Wu worked as a Data Science Intern at Duke University Nicholas School of the Environment in 2018. This internship lasted for three months and took place in the Raleigh-Durham, North Carolina area. During this time, Wu gained practical experience in data science applications within an academic environment.
Experience at IBM
Jade Wu was employed as an Associate Data Scientist at IBM from 2019 to 2020. This role spanned approximately 13 months and was based in the New York City Metropolitan Area. At IBM, Wu engaged in various data science projects, contributing to the company's analytics capabilities.
Internship at Georgia Institute of Technology
In 2019, Jade Wu completed a Data Science Research Internship at the Georgia Institute of Technology. This internship lasted for two months and took place in the Greater Atlanta Area. Wu's work involved research and analysis, further enhancing her skills in data science.
Education and Academic Background
Jade Wu earned a Bachelor of Science in Computer Science, Statistics, and Analysis from the University of North Carolina at Chapel Hill, where she studied from 2016 to 2020. Additionally, she attended the North Carolina School of Science and Mathematics from 2014 to 2016, where she completed her high school education. This academic background provided her with a strong foundation in data science and analytical methods.