Chenfei Song
About Chenfei Song
Chenfei Song is a Data Scientist at Condé Nast, where he has worked since 2021. He holds a Master's degree in Operations Research from Columbia University and has prior experience in data analysis roles at various companies, including JD.COM, Amazon, and Apple.
Work at Condé Nast
Chenfei Song has been employed as a Data Scientist at Condé Nast since 2021. In this role, he utilizes Spark for big data analytics, enhancing the company's data capabilities. He also employs Tableau to create interactive data visualizations that support decision-making processes. His contributions include involvement in data-driven projects that leverage machine learning and data mining techniques. Prior to his current position, he worked at Condé Nast as a Data Scientist for six months in 2020.
Education and Expertise
Chenfei Song holds a Master's degree in Management Science and Engineering from Tsinghua University School of Economics and Management, completed between 2018 and 2020. He also earned a Bachelor of Science in Statistics from Renmin University of China, where he studied from 2014 to 2018. Additionally, he participated in a term exchange program at The University of British Columbia, focusing on Mathematics and Statistics from 2016 to 2017. He furthered his education with a Master of Science in Operations Research at Columbia University in the City of New York from 2019 to 2020.
Professional Experience
Before joining Condé Nast, Chenfei Song gained experience as a Data Analyst at several prominent companies. He worked at JD.COM for three months in 2017, followed by a five-month tenure at Amazon from 2018 to 2019. He also had a brief role as a Data Analyst at Apple in 2019. Additionally, he served as a Financial Risk Analyst at KPMG China for three months in 2017. His diverse background in data analysis has equipped him with a strong foundation in SQL and Hive for managing and querying large datasets.
Technical Skills
Chenfei Song possesses expertise in various technical tools and platforms essential for data analysis. He utilizes AWS for scalable data processing and analysis, which enhances his ability to manage large datasets effectively. His proficiency in Spark and Tableau allows him to conduct big data analytics and create interactive visualizations. These skills support his work in data-driven projects at Condé Nast, where he applies machine learning and data mining techniques.