SUMMARY:

• Result oriented professional with over 7 years of cross industry experience as SAS programmer on different platforms - Windows and UNIX.
• Strong Experience of data analysis of Financial/Healthcare/Marketing and Manufacturing data and in the production of reports, tables, listing, and graphs on business and functional requirements.
• Experience and proficiency in SAS coding using SAS/BASE, SAS/SQL, SAS/MACRO, SAS/ODS, SAS/STAT, SAS/CONNECT, SAS ETL, SAS/ACCESS, SAS/GRAPH, in UNIX and Windows environments.
• Developed new or modified existing SAS programs to load data from the source and create business specific datasets.
• Experience with data cleaning, descriptive analysis, missing data analysis, data validations and preliminary data reporting.
• Thorough knowledge in all phases of data analysis, including definition and analysis of questions with respect to available data and resources, overview of data and assessment of data quality, selection of appropriate models and statistical tests and presentation of results.
• Excellent command in writing complex routines for data validations, data extraction, transformation and loading to target decision support systems using MS Excel, Pivot tables and SAS on various environments.
• Depth experience to perform all queries using databases like Oracle, Teradata, MS SQL Server, DB2 and MS Access.
• Involved in coding and pulling data from various database tables using Unions and Joins.
• Extensive work experience with Extract, Transform, and Load (ETL) from different database into SAS environment and SAS Enterprise Miner.
• Have strong knowledge about drop, keep, retain, and date manipulations, formats, informats.
• Extracting multi-million record file, data mining and analysis, created marketing incentive reports in SAS and exported to Excel spreadsheets, and pdf files.
• Hands on experience in SAS programming for extracting data from Flat files, Excel spreadsheets and external RDBMS (ORACLE) tables using LIBNAME and SQL PASSTHRU facility.
• Proven skills in creating excellent documentation, reports, tables, listings and graphs on business and functional requirements with SAS 9.2, SAS Enterprise Miner & Enterprise Guide
• Expertise in using various SAS report generating procedures like PROC REPORT, PROC SQL, PROC FREQ, PROC MEANS, PROC TABULATE, PROC TRANSPOSE and PROC PRINT.
• Customize the variables to user-defined formats using PROC FORMAT in printing reports.
• Experience in performing ad hoc queries for various application and reports on a daily/weekly or monthly basis
• Calculate the one-way frequencies, multi-way frequencies for counts of variables and table analysis using PROC FREQ with LIST, OUT, MISSING options.
• Skilled in using SAS Statistical procedures like PROC REPORT, PROC TABULATE, PROC CORR, PROC GLM, PROC ANOVA, PROC LOGISTIC, PROC TTEST, PROC FREQ, PROC MEANS, PROC UNIVARIATE, and PROC LIFETEST.

TECHNICAL SKILLS:

TOOLS: SAS 9.2, SAS Enterprise Minor, SPSS, Minitab, SAS/QC, Tableau, R (ggplot2), R Studio, SAP-ECC, MATLAB, MS Office (Access, Excel, Word, PowerPoint, Outlook, Project)

DATABASES: Oracle, MS Access & SQL Server, Netezza, Affinity, Teradata, Hadoop.

LANGUAGES & OPERATING SYSTEMS: SQL, C, C++, & MATLAB, VBScript, Python

Window family, UNIX & Linux.: SAS PROGRAMMING KNOWLEDGE

SAS Procedures: Experience working with SAS procedures such as PROC UNIVARIATE, PROC FREQ, PROC CORR, PROC REG, PROC ANOVA, PROC SQL, PROC GLM, PROC LOGISTIC, PROC GENMOD, PROC CATMOD, PROC DMREG, PROC VARCLUS, PROC TREE, PROC STDIZE, PROC SCORE, PROC SUMMARY, PROC DATASETS, PROC IMPORT/EXPORT, SAS ODS to create HTML, PDF, RTF. SAS Macros: Created complex and reusable programs for the purpose of data cleaning, validation, report generation, connecting to databases, date manipulation, and data integration. Used and created macro libraries to avoid redundancy.

STATISTICAL KNOWLEDGE: Descriptive Statistics, Inferential Statistics, Distribution Analysis, Confidence Intervals, Summary Tables, Histograms, Hypothesis testing: z-test, t-test, F-test (ANOVA), DOE, Six Sigma & SPC, Simple and Multiple Regression, Model Selection (Automatic, Stepwise) Outlier Analysis, Collinearity Diagnosis, Categorical Data Analysis ( Chi Square), Logistic Regression, Fault Diagnosis.

PROFESSIONAL EXPERIENCE:

Confidential, NY

SAS Programmer

Responsibilities:

• Involved in credit risk assessment model to calculate risk factor for individual clients based on hierarchy
• Developed complex SAS Macros to simplify SAS code and effectively reduce coding time
• Imported Data from relational database into SAS files per detailed specifications
• Imported data using LIBNAME and PROC SQL Pass -Thru facility to reduce processing time.
• Extensively performed Data Cleansing during the ETL’s Extraction and Loading Phase by analyzing the raw data and writing SAS Program and creating complex reusable Macros.
• Performed complex statistical analysis using PROC MEANS, PROC FREQ, PROC UNIVARIATE, PROC REG and PROC ANOVA.
• Carried out data extraction and data manipulation using PROC FREQ, PROC FORMAT, PROC MEANS, PROC SORT, PROC PRINT, PROC TABULATE, & PROC REPORT to create preferred customer list as per business requirements.
• Extensively used SAS procedures such as PRINT, REPORT, TABULATE, FREQ, MEANS, SUMMARY, TRANSPOSE and Data Null for producing ad-hoc and customized reports and external files
• Wrote SAS programs in UNIX platform.
• Developed programs in SAS to generate reports, creating RTF, HTML listings and reports using SAS ODS for ad-hoc and weekly report generation.
• Performed data analysis, statistical analysis, generated reports, listings and graphs using SAS tools e.g., SAS Integration Studio, SAS/Graph, SAS/SQL, SAS/Connect and SAS/Access
• Performed competitor and customer analysis, risk and pricing analysis and forecasted results for credit card holders on demographical basis.
• Utilizes advanced supervised and unsupervised learning methods of machine learning algorithm and statistical techniques like k-means clustering, principal component analysis (PCA), regression and visualization techniques for pattern recognition or data mining and classification of feature vectors using Python and R statistical computing environment.
• Programmed inPYTHONto explore the properties of small graphs, Reported viaPythontales expressions.
• Created reports in the style format (RTF, PDF and HTML) using ODS statements and PROC TEMPLATE
• Effectively prepared and published various performance reports and presentations.

Environment: SAS/BASE, SAS/MACRO, SAS/ETS, SAS/CONNECT, SAS Enterprise Guide, Teradata, DB2, ORACLE, SQL Server, UNIX.

Confidential, NY

SAS Programmer/Analyst

Responsibilities:

• Developed code to scrub population at account and household level for targeting for market campaigns.
• Involved with key departments to analyze areas and discuss the primary model requirements for the project.
• Documented methodology, data reports and model results and communicated with the Project Team / Manager to share the knowledge.
• Used SAS and SQL to perform ETL from Oracle and Teradata databases and created SAS datasets, SAS macros, Proc/data steps and SAS formats as required.
• Data processing and validations were done extensively on the SAS datasets using edit check programs.
• Developedreportsasperbusinessrequirementsandcreatedvariousreportslikesummary reports, tabular reports, excel reports etc.
• Converted programs from Teradata SQL to SAS to automate the monthly production processes.
• Developed new/modified macros for report generation using SAS/Macros as per business requirements.
• Designed and created SAS datasets from various sources like Excel datasheets, flat files, Oracle.
• Developed programs for statistical analysis and data displays.
• Worked on various SAS products SAS/BASE, SAS/SQL, SAS/STAT, SAS/ACCESS and SAS/MACROS etc. to develop solutions.
• Worked with complex datasets to extract customized reports using PROC SQL, PROC FREQ, PROC SORT, PROC REPORT, PROC MEANS for creating a preferred list of customers as per the given requirements from business analysts.
• Created new datasets from raw data files using Import Techniques and modified existing datasets using Set, Merge, Sort, Update, and conditional statements. Involve in Unix Shell programming using Bash and set up CRONTAB jobs for SAS application batch run.
• Wrote Korn-Shell Scripts performing various automation steps like running a SAS code, emailing the output files, removing and copying files, archiving files for historical data and zipping up files to send to external locations as attachments in emails.

Environment: SAS/ODS, SAS9.2, SAS Enterprise Guide, SAS/Macros, SAS/Graph, SAS/Access, SAS/Connect, SAS/Stat, Teradata, MS Excel, MS Access.

Confidential

SAS Programmer/ Analyst

Responsibilities:

• Worked as a SAS programmer for marketing targeting solutions- fulfilment team.
• Coordinated processes related to marketing campaign eligibility.
• Participated in campaign setup team meetings.
• Maintained and enhanced existing SAS reporting programs for marketing campaigns.
• Prepared audit statistics on providers and policyholders using various fraud detection techniques.
• Generated reports and analyzed on aggregate claims statistics.
• Developed predictive models to detect anomalies in claims.
• Extracted data from different sources like; Oracle, claims data mart, and text files using SAS/SQL, SAS/Access procedures and created SAS datasets.
• Performed data preparation and transformation using SAS procedures to ensure data quality and consistency.
• Generated reports on providers such as total amount billed, per-subject billing amounts etc. for auditors and investigators.
• Conducting analysis on client consumer databases looking at profitability, transaction behavior, and demographic characteristics.
• Providing segmentation for database marketing efforts, such as CHAID, cluster analysis, and customer profiling.
• Developed Excel tools for modelling accounting impacts of loss forecasts for CCAR and DFAST stress testing process.
• Built advanced regression techniques of machine learning algorithm: the techniques and methodologies utilized were Gaussian Process, Random Forest, Regression, Support Vector Machine, and Regularized logistic Regression, Ridge, and Locally Weighted Regression techniques in SAS, Python and R statistical computing environment.
• Responsible for statistical applications support and programming primarily in SAS, supporting Marketing team.
• Presentingdatausinggraphs,tables,chartsetc.
• Analyzed customer satisfaction survey for preparing strategies to improve customer loyalty.

Environment: BaseSAS9.2,SAS/EM,SASEGv9.3,SAS/Macros,SAS/SQL,SAS/ETL,SAS/Connect, Oracledatabase, MS Excel, MS Access, Windows, UNIX, OS/MVS, TSO, ISPF.

Confidential

SAS Data Analyst

Responsibilities:

• Extracted, transformed, and loaded data usingSAS.
• Wrote macros to develop a concise and reusable code.
• Converted large data from Oracle toSASdata sets by using SQL pass through and Libname facility.
• Wrote queries on the existing Oracle databases server to provide ad-hoc reports usingSASSQL.
• Extensively used PROC PRINT, PROC REPORT and PROC TABULATE for reporting.
• Merged the datasets to provide the users with the data in the required form.
• Interacted with other team members and lead to discuss the required developments to be made in coding to improve the functionality and effectiveness.
• Generated analysis reports, graphs usingSASReports andSASODS to produce Excel and HTML reports.
• Report various health care management metrics such as Number of readmissions, Patient category metrics, Patient demographics, service delivery and drug utilization etc.
• Created ad-hoc reports and graphs as per the requirements of the users.

  Submitted SQL Queries andSAScodes in UNIX shell to validate data.

Environment: SASBASE,SASGRAPH,SASACCESS, MS-Excel,SASODS, Oracle, UNIX and Windows NT.

Confidential

Statistical Analyst

Responsibilities:

• Setup and configured database generated from gage calibration and other quality measurement techniques (surface roughness, chemical analysis, microstructure testing, etc.) with queries involving relational data tables which presented right data at right time.
• Analyzed data using SAS 9.0 / SAS QC/ SAS EM to check process and quality variability and presented analysis geared toward identifying root cause of defects in the products.
• Performed root cause analysis and measured the severity of defects by drawing Shewhart charts: X and R charts, p charts, np charts, c charts, u charts, fishbone diagram, using in Excel, and SAS/QC.
• Executed ANOVA, DOE, hypothesis tests, Response Surface Analysis, and regression modeling for identifying and optimizing the major factors affecting the mold conditions by using SAS 9.2.
• Derived lean and six sigma, DMAIC, KAIZEN, 5S and developed Bar-chart, PERT/CPM, value stream mapping to reduce lead time, timely execution of the process, and to sustain continuous improvement of Process and Quality the products.

Environment: Base SAS, SAS/SQL, Minitab, Oracle, MS Access, Excel, Word, PowerPoint, Outlook, & Project.