Pi Jen (Byron) Tang
About Pi Jen (Byron) Tang
Pi Jen (Byron) Tang is a Senior Data Analyst at Unite Us, specializing in advanced analytics and predictive modeling. He holds a Master's degree in Business Analytics from the University of Minnesota and has extensive experience in data analysis and ETL processes across various industries.
Work at Unite Us
Currently, Pi Jen (Byron) Tang serves as a Senior Data Analyst at Unite Us, a role he has held since 2022. He joined the company following an acquisition and has been contributing to data analysis initiatives within the organization. His work involves leveraging advanced analytics tools and cloud platforms to enhance data-driven decision-making processes.
Education and Expertise
Pi Jen Tang has a diverse educational background. He earned a Postgraduate Diploma in Machine Learning and Artificial Intelligence from Columbia Engineering, studying from 2019 to 2020. He also holds a Master of Science in Business Analytics from the University of Minnesota - Carlson School of Management, completed in 2017. His undergraduate studies culminated in a Bachelor's degree in Business Administration and Management from National Chengchi University, which he attended from 2004 to 2008. Additionally, he studied as an exchange student at SGH Warsaw School of Economics in 2007.
Professional Background
Before joining Unite Us, Pi Jen Tang held several positions in data analysis and marketing. He worked as a Senior Data Analyst at Haworth Marketing + Media from 2017 to 2021 and as an Analytic Solutions Manager at Carrot Health, a Unite Us company, for four months in 2021. His earlier experience includes roles as a Senior Researcher at KANTAR TNS and a Marketing Associate at Porsche in Taipei City, Taiwan. He also worked as a Project Coordinator at Weber Shandwick and completed an internship in Business Analytics at Unilever.
Technical Skills
Pi Jen Tang possesses strong technical skills in data analytics. He is proficient in advanced analytics tools such as Alteryx and Spark, and utilizes cloud platforms like AWS and Azure for data analytics tasks. His expertise extends to developing and optimizing ETL processes and report automation pipelines. He is experienced in predictive modeling techniques, including regression, classification, and ensemble methods.