Sas Data

Penghua Wang

202-***-****

**-** **** **

Flushing, NY,11355

********@***.***

Summary

Over 4 years’ experience in analysis, design, development and testing in SAS.

Strong experience in SAS/BASE, SAS/STAT, SAS/MACRO, SAS/ACCESS, SAS/SQL in Windows Environment.

Solid background in performing business analysis like Customer behavior, Marketing Campaign and Risk Management.

Experience in import raw data with PROC IMPORT, INPUT Statement and INFILE Statement.

Strong skills with SAS/ODS to generate different forms of reports including RTF, HTML, PDF and MS Excel.

Hands-on experience of extracting data from database such as Oracle with SAS/ACCESS.

Experience of query, modifying and manipulating data, deleting duplicates, applying formats and labels with PROC SQL.

Experience in developing and debugging SAS/MACRO to extract, modify, merge and analyze data as well as generate

analysis output.

•Advanced skills in data quality management and data cleansing with PROC SUMMARY, PROC FREQ, PROC MEANS, PROC SORT, PROC UNIVARIATE as well as some DATA steps like ARRAY, MERGE, SET, etc.

•Strong background in predictive modeling using SAS modules for Linear, Nonlinear, Logistic, GLM, Mixed, Time Series, Segment analysis etc.

•Rich experience in SAS Marketing Research and Business Analytics through data mining, optimization, and decision tree etc.

•Excellent in oral and writing communication skills in English

•Strong ability in independent work and teamwork

•Proficient with MS Excel, PowerPoint, Word.

Technical Skills

•SAS Skills: SAS/BASE, SAS/STAT, SAS/MACRO, SAS/SQL, SAS/ACCESS, SAS/ODS, SAS/GRAPH

•Database Skills: Oracle, ACCESS

•Language: SQL, Python,

•Design Tools: MS Excel, Power Point, Word, LaTeX

Certificate

SAS Certified Base Programmer for SAS 9

SAS Certified Advanced Programming for SAS 9

SAS Certified Statistical Business Analysis Programming for SAS 9

Work Experience and Projects

Market Research Analyst, Acoustic Audio LLC Jan 2014 – Aug 2017

•Using time series analysis--ARIMA procedure, Autocorrelation, white noise to check whether there is any trend

•Using linear regression models with/out intercept, checked by T-test, F-test, p-values, R-squares, residual plots, goodness of fit, Significance of parameters, graph of the candidate model to decide the fitted mixed linear model;

•Using the appropriate (time series, linear regression, logit regression ect.) model to predict the market demand;

•Statistical Methods: Time Series Analysis and Modeling, Linear Regression Modeling, logit Regression, Nonlinear Regression Modeling, Goodness of Fit, Statistical Prediction.

•SAS procedures: proc print, proc reg, proc plot, proc gplot, proc univariate, proc sort, proc test, proc ARIMA, proc nlin, proc SQL (merge, delete, overlay, sort,do loop, if-then do, if-then delete, if-then, do-to-), SAS MACRO

•Short-Term Forecast of the Monthly Foreign Exchange Rate;

•STATISTICAL METHODS: Time Series Analysis and Forecasting, Time Series Transformation, Time Series Plot, Log(y), Diff(y), Augmented Dickey-Fuller Test, diff(log(y)), ACF, PACF, EACF, AR, ARMA, MA, Model Selection by AIC, AICc, BIC and their Coefficients, Diagnosis of ARMA/AR/MA models, Normal QQ plot, Residual Analysis, Test for Outliers, Forecasting, Error Ratio Analysis.

Education

•MS in Statistics, George Washington University, Washing, DC

•BS in Mathematics, Pittsburg State University, Pittsburg, KS

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