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Sas Analyst Resume



  • SAS Certified Professional wif 7 years of experience working as a SAS Analyst on Unix and Windows environment.
  • Experienced and certified in Oracle technologies including Advanced Oracle SQL Certification.
  • Strong experience wif Excel using VLOOKUP’s, Pivottable’s, Charts, Arrays, Sparkline’s, Outlining, Customized reports.
  • Worked wif different test environments including DIT, SIT, QA and UAT phases and has experience working wif both functional and non - functional testing (NFT) and preparing teh product or service as per teh Operational Acceptance Testing (OAT) especially for non-functional testing.
  • Involved in teh development of test plans, test scenarios and test strategies to facilitate teh process of testing. Also involved in Analysis, Design, and Functional Specifications to identify Test Requirements, Design Test Cases, Test Scripts, and Test Data wif expected output.
  • Responsible for creating and updating Business Requirement and Functional Requirement documentation and serving as liaison between teh business team and developer.
  • Good understanding of Anti Money Laundering (AML), Compliance and Bank Secrecy Act regulations. Has also completed post-graduation in Banking and Finance in this regards.
  • SAS Certifications cleared in Base SAS 9.3 and Predictive Modeling using Enterprise Miner 13.
  • Demonstrated ability to understand business requirements and processes and also learn new technical tools and software applications, and work wif a variety of data and data sources.
  • Worked wif SAS DataIntegration Studio to develop/automateETL Processes and involve in Error Handling in SAS.
  • Strong experience wif ETL and DW concepts. Has been part of Data migration and ETL testing projects. Experience performing QA validation and checking for duplicates, removing duplicates and checking for data validation and verification.
  • Experience in Data Validation, Data Scrubbing, Data Cleaning, Data warehousing and Statistical reporting using statistical procedures like Proc Freq, Proc Means, ProcUnivariate.
  • Experienced wif Unix Shell Scripting and creating datasets in SAS using Unix.
  • Developed and modified existing SAS programs as well as imported data using SQL Pass Through and Libname engine methods to create tables and extract data from teh Teradata and Oracle DB.
  • Trained in Good Manufacturing Practices (GMP’s), GS1, Regulatory Compliances and FDA Guidelines including CFR 21. Hold a Master’s degree in Packaging Science specializing in Food and Pharma Packaging and Logistics.
  • Experienced wif SAS Visual Analytics Data Builder, SAS Visual Analytics Explorer, SASVisual Analytics Reports Designer modules. Used SAS Visual Analytics for preparing, exploring, analyzing, and interpreting data. Results were halpful for understanding customer behavior analysis, customer profiling, market segmentation, generating trend analysis etc. Good understanding of SAS Visual Analytics Designer module.
  • Worked wif SAS Predictive Modeling for preparing data, building predictive models, assessing models, scoring new data sets and implementing models. Certified Predictive Modeler and good noledge wif Linear and Logistics regression, ANNOVA, Standard deviation, Time Series models, pricing and payment models.


Languages: SQL, SAS, PLSQL, JAVA

Tools: Oracle Developer, SQL Server, SAS 9.4, SAS Enterprise Guide 13, SAS Enterprise Miner, SAS Visual Analytics 7.3 - Data Builder, Explorer, Reports module, SAS Management Console, LASR Server, MS Excel, MS Visio, Jira, ALM.

Operating System: Unix, Linux, Windows


SAS Analyst

Confidential, NY


  • Extracted, manipulated data, and created Data Sets from various sources like Excel, flat files, Oracle database, Access database using PROC IMPORT techniques and SQL pass through facility and performed SAS data manipulations against teh resulting sets.
  • Involved wif requirements gathering, updating BRD’s, creating visio’s and providing suggestions/recommendations to client to improve teh product. Working wif Agile and Scrum methodologies and working in smaller, achievable and well defined Sprint Cycles. Involved wif conflict resolutions and updating Product Owner about any Product Backlog.
  • Documented business requirements, gap analysis, and future state workflows. Documented and maintain a tracker for tasks and projects as well as documented system design, functional, and technical specifications.Developed test cases, use cases, test plan, and test scripts for various releases and enhancements.
  • Engaging wif customers and AD Team on a daily basis for SIT/UAT Phase Testing review along wif attending calls for QA/UAT testing review and halping teh QA team resolve any issues/concerns.
  • Participating in Root Cause Analysis meetings/discussions for defects review.
  • Communicated status and assignments to Project Manager and Project Team and involved in UAT sign off activities.
  • Making teh client/developers aware of any concerns/issues that occur during teh SIT/UAT Testing phases.
  • Engaging wif customers on a daily basis for SIT/UAT Phase Testing review along wif attending calls for QA/UAT testing review and halping teh QA/UAT team wif any issues/concerns.
  • Participating in Root Cause Analysis meetings/discussions for defects review.
  • Publish Daily Test status RDMS reports / defect metrics for teh client to review/discuss on a daily basis and create formulae in Dashboards in QC to generate specific reporting data as per client requirement. eg: Total Open Defects Summary List.
  • Involved in teh development of test plans, test scenarios and test strategies to facilitate teh process of testing. Also involved in Analysis, Design, and Functional Specifications to identify Test Requirements, Design Test Cases, Test Scripts, and Test Data wif expected output.
  • Reviewed teh data mapping document regularly for ETL testing and generated customized queries using SQL to verify teh requirements. Generated high level test scenarios for testing each phase and then wrote descriptive test cases for each phase and logged defects in ALM and Jira.
  • Verified data on Source and Target side of ETL, verified data completeness and transformation rules, tested referential relation and integrity of data as per requirement specification documentation, checked for duplication of records and/or data errors. Performed QA validation on various business rules and transformations including checking for duplicates, deleting duplicates, performed QA data validation and verification and ensured data is correctly migrated to teh DataWarehouse. Involved in automation of ETL batch jobs and involve in errorhandling of SAS and SQL code.
  • Extensively used Excel for VLOOKUP’s and Pivot tables to generate customized reports for client and halp wif immediate firsthand identification of problems.
  • Verified teh excel results wif results generated from SQL and SAS. Developed, implemented, and facilitated process for data identification, segregation, and cleansing of data as well customized results using through excel pivot tables and Vloop’s.
  • Created SAS datasets through Unix environment using Unix Shell Scripting.
  • Generated tables, listings and graphs using Proc Means, Proc FREQ, Proc TRANSPOSE, Proc REPORT,
  • Created data set specifications or programming specifications in SAS, SQL in accordance wif project requirements and good documentation and programming practices.
  • Produced quality customized reports using PROC REPORT and also provided descriptive statistics using various procedures like ProcFreq, Means and Univariate procedures.
  • Performed Root Cause Analysis, identified patterns and perform trend analysis and contributed towards teh implementation of teh Data Management policies.
  • Involved in data verification, data manipulation and coding activities including teh usage of basic and standard SAS procedures and Macro coding. Used SAS Macros coding for handling several repetitive tasks and avoided extensive coding.
  • Good exposure using SAS and proc sql including concatenation, merging, user defined formats, group by, joins, rank, sorting, removing duplicates etc.
  • Involved inverification of programming logic by overseeing teh preparation of test data, testing and debugging of programs.
  • Generated tables, listings and graphs using PROC MEANS, PROC FREQ, PROC SUMMARY, PROC TRANSPOSE, PROC REPORT, PROC GCHART and PROC GPLOT Procedures.
  • Generated output files in teh form of listing, HTML, RTF and PDF formats using SAS ODS.

SAS Analyst

Confidential - San Francisco, California


  • Worked wif Project Managers design, execute, and document data management and quality assurance procedures for research data collection projects using SAS and other statistical packages.
  • Supported research efforts by reviewing statistical methodologies, recommending methodological best practices and implementing statistical analysis solutions
  • Involved wif Data Migration and ETL testing project using complex SQL queries. Used various SQL queries including Joins, Union, Aggregate functions, Group by, Inline views, transpose for validating data.
  • Using teh data mapping document or teh requirements document, created detailed test cases for each phase of teh ETL process. Teh test cases checked for teh required columns, old versus new changes, data integrity etc. Teh test cases included detailed description, expected versus actual results comparison etc.
  • Submitted daily status report to client using excel pivot tables and vlookup. Created excel pivot tables and charts using worksheet data and external resources, modified pivot tables, sorted items and group data, and refreshed and formatted pivot tables.
  • Collaborated wif project team members on sample selection, study design, and statistical analysis related to survey methods.
  • Developed datasets and ad hoc reports used for sample analysis using SAS and other statistical packages.
  • Developed and designed methods, procedures, and specifications for collecting, organizing, interpreting, classifying and reporting on complex information for computer input and retrieval, utilizing noledge of database construction and retrieval methods.
  • Performed risk based approach as per FDA expectations for determining teh level of validation and documentation appropriate for SAS programs.
  • Provided analyses and descriptive reports of project data for management of research projects. Document, program, debug, and run a variety of scheduled and ad hoc processes, summaries, statistics, and other electronic reports.
  • Manipulated and managed very large data files in SAS as well as developed SAS Macros for processing, and extensively used proc SQL and Base SAS for analyzing and reporting on trend analysis.
  • Prepared final datasets for project deliverables. Specifically, compiled, cleaned and ensured teh quality of datasets delivered to clients. Documented quality assurance operations performed in final reports, and provide basic documentation on datasets.
  • Collaborated wif Project Team members and Operational staff to identify and resolve serious technical problems; take teh lead in diagnosing problems, including programming, data and procedural errors.
  • Created customized and presentation-quality reports from data analysis results. This includes presenting summary tables and figures.
  • Applied quantitative methods and techniques to manage and analyze research data, as well as perform advanced statistical analysis.

SAS Developer/Market Analyst



  • Developed and automate daily, weekly, monthly, and seasonal reporting/scorecards using SAS and SQL to monitor teh health of teh eCommerce business as well as share business insights wif marketing, product development, sales, and finance stakeholders.
  • Used Survey Select procedure along SURVEY Means, SAS Survey Freq procedures,which provides a variety of methods for probability sampling.
  • Exceptional use of opinion polls surveys questionnaires demographics and statistics for collecting relevant data for market survey. Used SAS proc SQL and SAS Macros to generate customized reports and avoid and repetitive coding.
  • Using Excel pivot tables to manipulate large amounts of data in order to perform data analysis, position involved extensive routine operational reporting, hoc reporting, and data manipulation to produce routine metrics and dashboards for management.
  • Used predictive modeling analysis for handling probability based complex designs including stratified selection, clustering and unequal weighting.
  • Used sample survey method to obtain information about a large population by selecting and measuring samples from teh population. Used imputation methods to take care of missing values from Survey data.
  • Ensured data integrity and testing processes are followed for reporting and research tools. Worked wif internal and vendor support teams to report and resolve data discrepancies.
  • Partnered wif internal and external Information Technology teams to develop short and long term data analytics infrastructure.
  • Supported data and analytics requests throughout teh development cycle including gathering data requirements, sourcing and validating data, analyzing data, building models, synthesizing insights, and presenting results for market research survey data.
  • Supported analysis across multiple large-scale data sources (structured and unstructured) to identify and socialize key facts and insights from wifin teh ecommerce channel.
  • Uncovered insights from exploratory analysis by leveraging data experiments and appropriate measurement tools for market survey data.
  • Applied multivariate statistical tools to halp build predictive models, improve customer segmentation, optimize approach to online pricing, and improve elements of teh digital marketing mix.
  • Developed, measured, analyzed and reported all key performance indicators for HL’s online sales channels. Developed and executed performance dashboards as well as performed ad hoc and recurring analyses on market survey data.
  • Analyzed performance and impact of digital marketing and merchandising investments wif key e-retailer accounts to determine customer impact and return on investment (ROI) (for both online and in-store purchases) using sampling market research strategies and tracking and arranging survey data.Proactively identified conversion breakdowns on key e-retailer sites by analyzing clickstream data and purchased funnel metrics; developed and tested new methodologies, technologies, or approaches to find potential conversion improvement opportunities through coordinated market survey analysis.
  • Identified business growth opportunities via data driven insights. Developed actionable recommendations and present them to eCommerce and Business Unit leadership.
  • Using SAS PredictiveModeling created data sources in Enterprise Miner, explored and assessed data sources, build predictive models using regression analysis (linear and logistics), decision trees and neural networks, used fit statistic for different predictions, used decision processing for adjusting over sampling, used profit/loss information for assessing model performance and for comparison of models, market segmentation, customer behavior analysis, market research survey data.

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