Jessie Tang
About Jessie Tang
Jessie Tang is an Associate at Analysis Group with extensive experience in research and data analysis, specializing in advanced statistical techniques and programming languages.
Current Role at Analysis Group
Jessie Tang has been serving as an Associate at Analysis Group since 2017. Based in Boston, Massachusetts, Tang engages in various analytical and research projects, utilizing their extensive background in statistical analysis and data modeling to support the team's objectives.
Previous Experience at Boston University
From 2012 to 2014, Jessie Tang worked as a Research Assistant at Boston University, also located in Boston, Massachusetts. During this period, Tang developed essential research skills and gained valuable experience in the field of environmental engineering and statistical analysis.
Doctoral Research at Harvard University
Jessie Tang conducted doctoral research at Harvard University from 2012 to 2016 in Cambridge, Massachusetts. This role involved deep engagement in environmental health research, contributing to several significant academic projects and publications.
Educational Background
Jessie Tang's educational background includes a Master of Science degree from the Harvard T.H. Chan School of Public Health (2010-2012) and a doctoral degree from the same institution (2012-2016). Additionally, Tang earned a Bachelor of Engineering in Environmental Engineering from National Taiwan University (2006-2010).
Technical Skills and Expertise
Jessie Tang possesses proficiency in numerous statistical tools and programming languages, including R, SAS, MATLAB, ArcMap, SQL, iPython notebook, C, Python, Java, HTML, and CSS. Specialized in advanced feature selection techniques like LASSO, Elastic Net, and Bayesian Kernel Regression, Tang is skilled in various modeling techniques including Kriging, Mixed Effects, Penalized Splines, and Land Use Regression. Tang also conducts complex analyses such as Time-series, Longitudinal, Trend, and Spatial-Temporal Analyses, and is adept in data visualization using tools like ggplot2, R Shiny, and Graphlab create.