Statistics, Analysis, R, SQL, Python, SAS, Data Virtualization

Zhenning Kang

413-***-**** **** Center Street, Culver City, CA, 90232 ************@*****.***

EDUCATION

University of Massachusetts Amherst MA, USA

Master of Science in Bio-Statistics Expected 05/2018 Shanghai University of International Business and Economics Shanghai, China Bachelor of Business Administration 09/2008 06/2012 COURSES

GPA 3.95/4.0, Statistics, Advanced Statistical Computing(SQL, Spark), Modern Applied Statistical Methods(R), Applied Regression Modeling(R), Bayesian Analysis(R, JAGS), Mixed Model(SAS), Survival Analysis(R, SAS), Categorical Data Analysis(R), Machine Learning(Python) EXPERIENCE

Research Assistant Social and Economic Impacts of Gambling in MA (SEIGMA) 09/2017--Present University of Massachusetts Amherst (UMass)

Teaching Assistant School of Public Health & Health Sciences (SPHHS) 09/2016--09/2017 Applied Regression Model (BioStat 650), Telling Stories with Data (PubHlth 490) Statistical Consultant Statistical Consulting and Collaboration Services (SCCS) 09/2016--12/2016 Department of Mathematics and Statistics

PROJECTS

Data Analysis and Virtualization with Shiny (R, Shiny) on-going

Analyzed secondary data to triangulate and add insight into a multi-year research on the economic and social impacts of introducing casino gambling encouraged by Massachusetts Gaming Commission (MGC).

Designed interactive map and dashboard to enable boarder audience can interact with info on demographics, educational attainment and property rates statewide in tables, plots and maps among different communities.

Applications shared through shinyapps.io and codes available to public on github.com. Global Classification of Abortions by Safety (R) 05/2016--09/2017

Developed a Bayesian hierarchical model to estimate the global, regional, and sub regional distributions of abortion by safety based on empirical data from the abortion methods, providers, and other covariates. .

Applied Deviance Information Criterion (DIC) for in-sample fit and tested on about 20% training sets to validate out-of-sample model performance for comparison of estimates across 16 models.

Published results on The Lancet on September 27, 2017 with collaboration from experts in UNDP/ UNFPA/ UNICEF/WHO/WB and other institutes and universities. Statistical Consulting (R) 09/2016--12/2016

Provided statistical advises for researchers from UMass, local governments, non-profits and external, for-profit entities to fulfill their needs with study design and analysis plans, performing data and analysis, interpreting results or preparing grants and publications.

Cooperated with faculties from the Department of Mathematics and Statistics. Analysis of Occupancy Detection (R, MATLAB) 02/2016--04/2016

Applied machine learning methods to replicate the analysis of occupancy detection from Candanedo and Feldheim (2015) to regulating heating, ventilation and air-conditioning costs.

Methods including logistic regression, linear discriminant analysis (LDA), classification and regression trees (CART), random forest (RF) and support vector machine (SVM).

Concluded that SVM model with all predictors generated the highest accuracy. SKILLS

Programming Languages: R, Python, SAS, MATLAB

Techniques and Tools: SQL, ShinyApp, Spark, Hadoop, LaTex

Contact this candidate