** ****** *****, ***. ** Newark, DE, *****

Tel: 302-***-****

E-mail: rdiyrt@r.postjobfree.com

Objective

Analyst/Programmer with emphasis in data analysis, modeling and programming

Education

M.S. in Statistics, University of Delaware (GPA: 3.96/4.00) May.2010

B.S. in Statistics, Nankai University, China Jun.2008

Thesis: Analysis Report of Educational Strength in Regions of China

Professional Exams:

 SAS Certified Advanced Programmer for SAS 9(Score: 100%)

 Microsoft Certified Technology Specialist:

SQL Server 2008, Database Development (Score: 100%)

 Society of Actuaries Probability Exam

Computer Skills

 Proficient: SAS (Base, Macro, Graph, STAT and ODS), SQL, MS office, Windows

 Intermediate: VBA, R, Minitab, JMP, C++, FORTRAN, UNIX

 Basic: MATLAB, HTML, SPSS, Linux

Working Experience

Statistical Analyst Intern, DuPont Crop Protection, DE Jun.2009-May.2010

 Contributing member of a small high-energy statistics group providing statistical design and analysis support for crop protection product discovery, field development and regulatory science efforts. Statistical methods used including linear/logistic regression, multivariate analysis, experimental design and etc

 Using SAS macro code, Excel (including VBA), JMP and Minitab to provide accurate and statistically appropriate graphs, tables and model results for diverse types of analyses and developed/optimized relative project protocols

 Wrote and validated complex SAS macro code for data summary and report

 Participated in project meetings and consultations with scientists and project managers for project background communication and results interpretation

Research Assistant, University of Delaware Jan.2009-May.2009

 Helped the advisor to plan and conduct the economic experiments and programmed the supporting software independently

Honor & Awards

 Member, Golden Key International Honour Society (top 15% of the graduate study)

 Won first prize in Statistics Seminar project, University of Delaware 2008

 Excellent Students Scholarship, Nankai University, China 2004-2008

28 Marvin Drive, Apt. B2 Newark, DE, 19713

Tel: 302-***-****

E-mail: rdiyrt@r.postjobfree.com

Statistical knowledge

Probability Theory Mathematical Statistics Applied Database Management/SAS Regression Analysis Logistics Regression Experimental Design

Time Series Analysis Sampling Techniques Multivariate Analysis

Relative Projects Experience

Diverse types of SAS projects

 Demonstrated programming skills through wrote and validated many SAS macro codes

 SAS procedure used: reg, glm, anova, mixed, logistic, genmod, factor, princomp, cluster, tree, discrim, arima, sql, sort, corr, import, export, format, contents, datasets, surveyselect, iml, compare, ttest, univariate, tabulate, report, freq, means, gplot, gchart, boxplot and etc

Screen validation for crop protection product (using JMP, Minitab and Excel)

 Assessed reproducibility and reliability of discovery bioassays through quality control

 Optimized relative protocol

Global insect susceptibility monitoring project (using Excel VBA and Minitab)

 Leadership role overseeing data entry of bioassay data

 Analyzed the data using like box plot and scatter plot

Developed VBA software (using Excel VBA)

 Added functions like p-value for the model based on the client’s requirements

 Corrected mistakes in the software

Blue Nile Diamond Price Modeling (using SAS and JMP)

 Stratified sampling method was used to collect the data sample of diamond price

 Coded the key price determinants (Carat, Clarity, Color, Cut) into dummy variables

 Build both log-linear and nonlinear model to predict the diamond price

HyTex Company Direct Marketing Catalog Data Analysis (using SAS)

 Using stepwise method to select key variables and build multiple regression linear model

 Proposed proper marketing strategies for the company

Analysis of Educational Strength in Regions of China (using SAS)

 Cluster Analysis was used to classify the educational strength of China’s provinces

 Ranked China’s provinces’ educational strength based on method of factor analysis

 Suggestions are made to enhance the overall educational strength of China

U.S. Public Utility Data (using R)

 Found the relationship between variables by principal component analysis and Biplot

 Chose a proper number of principal components to explain through scree plot, total variance explained and eigen values

Data Simulation (using SAS and R)

 Compared the precision of two estimators based on simulated data sets

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