NAN ZHANG
******@****.***.*** • Phone:919-***-****
Durham, NC
A statistical analyst with three years of work experiences is searching for positions, which require:
• Solid and broad background in statistics; creative thinking in the application of statistical methods into different fields;
• Proficient skills in SAS programming (with Base and Advanced Programmer Certificate for SAS 9);
• Ability to learn quickly and multi-task problem solving;
• Excellent skills in organization and communication and ability to work either independently or collaboratively
• Experience in analyzing multiple data;
WORKING EXPERIENCE
Statistical Consultant, UNC Eshelman School of Pharmacy, NC (February 2014 - May2014)
• Worked independently on a
statistical consulting project aiming to evaluate the effectiveness of community pharmacist s-initiated intervention on proportion of day
coverage (PDC) score in adherence to diabetes medication. PDC is one criterion for Part D star ratings evaluation.
• Completed data
management by using SAS/BASE, and accomplished data analysis with logistic regression and multiple linear models by using SAS/STAT
(proc reg, proc logistic, proc glm), SAS/Macro.
• Presented a final report and
interpreted final results in professional tables and figures created by SAS/GRAPH and SAS/TABULATE.
Analyst (part-time), Uconnection.com, Chapel Hill, NC (September 2013 - January 2014)
• Explored index variables
that influence the rating of restaurants.
• Utilized SAS and Excel to
manage client survey data from over 70 restaurants around UNC at Chapel Hill.
• Created indices for major,
gender and class of clients and employed logistics regression and linear mixed model to mine the survey data .
Research Assistant, Beijing Branch of BioChain Science&Technology, Inc., China (July 2010 - January 2011)
• Applied statistical analysis
in DNA methylation study of preclinical projects. Established associations between de-methylations within promoter-specific regions and
three methylation inhibitors (5-Aza-cytidine, Bix-01294 and Leptomycin B) in four colon cancer cell lines.
• Involved in the completion
of data management, data quality checking, and statistical analysis for all aspects of bio-medical research, ranging from basic science and pre-clinical
studies to genetic.
Research Assistant, National Engineering Research Center for Beijing Biochip Technology (CapitalBio Corporation), Beijing, China
(August 2007 - January 2009)
• Utilized R to manage
complex microarray data from experiments, and performed quality control test for programming plans.
• Utilized R to perform
supervised and unsupervised clustering, T-test, Wilcoxon rank sum test and ANOVA analysis for DNA methylation microarray data, in
order to identify methylated colon cancer-specific genes.
• Applied lowess
normalization and significance analysis of microarrays (SAM) statistical software to analyze gene expression microarray data, in order to
identify differentially expressed genes in HeLa cells after stimulated with chemical extraction from Cordyceps (a traditional Chinese
medicine).
RELEVANT COURSE PROJECTS
• Project (Finance) – Applied GARCH modeling for analyzing portfolio performance selection. Utilized R to manage and analyze
the data on dollar-denominated Morgan Stanley Capital International (MSCI) stock market indices for Asian, North American and
European markets. Collaborated work with two classmates by using both unconditional and conditional portfolio selection and suggested
investing heavily in the North America index.
• Project (Clinical trial) – Employed Kaplan Meier method and Cox Proportional Hazard Model to evaluate whether, among people who
were depressed after having a heart attack, treatment for depression and other risk factors would lessen or slow the rate of repeat heart attacks or
death. Used SAS data step to manage three raw data sets into a joint data set and wrote programs in SAS statement. The results indicated that the
treatment for depression effectively lessened the rate of repeat heart attacks.
• Project (Clinical trial) – Used Cox Proportional Hazard Model to explore differences in the rate of HIV infection among three hormonal
contraceptives treatments and to identify risk factors associated with the infection. Effectively managed data using SAS by performing multiple
imputations for missing data, data merging and transposing to formatted analysis datasets. Managed over 5000 participants while ensur ing the
consistency. Interpreted results in professional tables and figures. The results illustrated that among three contraceptives, IUD group has the highest
HIV rate. In addition, among all the factors that have been collected, marital status is highly associated with HIV infection.
SKILLS
• Perform generalized linear regression model, survival data analysis, longitudinal data analysis, categorical data analysis and multivariate
data analysis by using SAS
• Calculate power given sample size or estimate sample size given a power value
• Import data from various formats (e.g. CSV and Excel) into SAS datasets
• Use analytical procedures such as SAS Base, SQL, Macros, ODS and SAS Graph
• Generate statistical tables, graphs, and reports in SAS and interpret results
• Use other software such as R, STATA, Microsoft Office and Photoshop
EDUCATION
• M.S. in Statistics
University of North Carolina at Chapel Hill
2014
• M.S. in Biomedical Engineering
Yanshan University
2009
• B.S. in Bioengineering
Yanshan University
2005
CERTIFICATE
• Certified Base Programmer Credential for SAS 9
• Certified Advanced Programmer Credential for SAS 9