Zian Fan
About Zian Fan
Zian Fan is a Data Science Intern at Rakuten Advertising, specializing in data storytelling and visualization. He holds a Bachelor's degree in Mathematical Statistics and Probability from the University of California San Diego and a Master's degree in Applied Data Science from the University of Southern California.
Work at Rakuten Advertising
Zian Fan has been working as a Data Science Intern at Rakuten Advertising since 2021. This role involves conducting data analysis and utilizing various data science techniques to support business objectives. The internship is conducted remotely, allowing for flexibility in work arrangements. Zian applies skills in data analysis and visualization to enhance the company's data-driven decision-making processes.
Education and Expertise
Zian Fan earned a Bachelor of Science in Mathematical Statistics and Probability from the University of California San Diego, studying from 2018 to 2020. Following this, Zian pursued a Master's degree in Applied Data Science at the University of Southern California, completing the program from 2020 to 2022. This educational background provides a strong foundation in statistical analysis and data science methodologies.
Technical Skills and Tools
Zian Fan possesses expertise in managing databases using SnowFlake, MySQL, and MongoDB, along with experience in cloud computing through AWS EC2. Zian employs data mining techniques with Apache Spark and Apache Hadoop, showcasing proficiency in handling large datasets. Additionally, Zian utilizes programming languages such as Python, R, and MatLab for machine learning modeling, enhancing analytical capabilities.
Data Analysis and Visualization Techniques
Zian actively seeks to enhance skills in data storytelling and visualization. This includes conducting explanatory analysis using tools like Tableau, R Shiny, and Google Analytics. By focusing on data visualization, Zian aims to communicate insights effectively, making complex data more accessible to stakeholders and supporting informed decision-making.