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Pengyi Sun

Head Of Data Science at Vista

Pengyi Sun has extensive work experience in data science and analysis. Most recently, as the Head of Data Science at Vista Global, they lead a team of data scientists and engineers to extract key information from contracts and create personalized pricing models. Prior to that, they worked at JetSmarter, where they utilized data science and mathematical modeling to develop pricing strategies and revenue management systems. They also have experience as a Data Scientist at Sears Holdings Corporation and a Pricing and Revenue Management Specialist at Spirit Airlines. Additionally, Pengyi Sun has worked as a Data Scientist at The Strategic Group, a Teaching Assistant at the University of Florida, and a Software Engineering Intern at the Chinese Academy of Sciences.

Pengyi Sun's education history is as follows:

Pengyi Sun obtained a Bachelor's degree in Applied Mathematics from Tsinghua University from 2002 to 2006. Pengyi then pursued further education and completed a Master's degree in Statistics from the University of Florida from 2006 to 2009. Subsequently, they obtained a PhD in Quantitative Finance from the University of Florida from 2006 to 2012. In addition, they also acquired an MBA in Finance and Security Analysis from the University of Florida - Warrington College of Business in 2011 and 2012.

Pengyi Sun has also earned several certifications in various fields related to data analysis and machine learning. These certifications include "Machine Learning for Trading Specialization," "Reinforcement Learning for Trading Strategies," and "Using Machine Learning in Trading and Finance." These certifications were obtained from Coursera Course Certificates in June 2020. Additionally, they completed several Coursera Verified Certificates in data science topics such as "Developing Data Products," "Practical Machine Learning," "Regression Models," "Exploratory Data Analysis," "Reproducible Research," "Statistical Inference," "Getting and Cleaning Data," "R Programming," and "The Data Scientist's Toolbox" in the years 2014 and 2014, respectively.

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