SUMMARY

• Statistical Analyst/Programmer with over 6 years of experience in analysis, design, development, testing and implementation of Applications in Financial, Retail and Healthcare Industry using SAS.
• Certified Base SAS programmer for SAS 9.
• Extensive experience in SAS programming on different platforms - Windows NT, UNIX Solaris.
• Identified project scopes and facilitated meetings for business requirements gathering and architected to-be business and systems processes for different projects
• Experience in working with SAS Enterprise Guide Software (4.1 & 5.1 versions) for reporting and analytical tasks.
• Good experience with PC SAS, SAS Enterprise Miner & Enterprise Guide.
• Extensive knowledge of Banking, Health Care, Retail and Campaign marketing data.
• Adept in BaseSAS, SAS/MACROS, SAS/SQL, SAS/GRAPH, SAS/ACCESS, SAS/STAT, SAS/IntrNet, SAS/CONNECT and SAS/ODS etc. in Windows & UNIX environment.
• Experience in PROC SQL joins and PROC SQL set operators to combine tables
• Efficient in utilizing SAS Functions, SAS Procedures (PROC UNIVARIATE, PROC SURVEYSELECT), Macros, and other SAS application for data updates, data cleansing and reporting.
• Competent in developing programs to generate derived datasets from raw data imported from various sources.
• Strong in Data management, data extraction, manipulation, validation, and analyzing huge volume of data.
• Expert in transforming data imported from different data sources into analysis data structures, using SAS functions, options, ODS, macro facility and other SAS procedures.
• Experience in extracting data from relational databases like Oracle, DB2, Teradata, SQL Server and MS Access etc.
• Sound in Developing and designing SAS Programs / Macros to access and analyze financial data.
• Experience using statistical language such as R, Matlab, and Mathematic for developing and documenting quant models.
• Experience in working with Business Users and Technical Teams to understand requirements and to develop code based on SDLC procedures.
• Expertise in automation of SAS processes, models and reports using SAS tools.
• Excellent Visual representation of data using Tableau, Excel and communicating analysis to all levels of business users within the organization.
• Proficient in transferring data across different environments using FTP, SFTP, Humming Bird and Synchrony.
• Well versed in writing UNIX/LINUX shell scripts.
• Fluent in statistical and machine learning algorithms such as decision trees, neural networks, collaborative filtering, clustering, survival analysis, graph theory, etc.
• Proficiency in Time Series Forecasting techniques (ARIMA, ARCH/GARCH) using SAS Enterprise Miner.
• Ability to work efficiently in both independent and team environments, worked with Project Managers, Team Members / Associates, Statisticians, Business Analysts.
• Analytical, organized, enthusiastic to work in a fast paced and team oriented environment
• Strong communication skills, problem solving skills and challenge oriented.
• SAS Programming experience in Mortgage, Data Analysis, reporting, Production Jobs, SAS macros, SAS Programming, SQL, Mortgage, Data Analysis, reporting, BASESAS, SAS 9.13, Excel, Production Jobs, SAS macros SAS Programming, SQL, Mortgage, Data Analysis, reporting, BASE SAS, SAS 9.13, Excel, Production Jobs, SAS macros SAS Programming, SQL, Mortgage, Data Analysis, reporting, BASE SAS, SAS 9.13, Excel, Production Jobs, SAS macrosSAS Programming, SQL,

TECHNICAL SKILLS

Statistical: SAS Enterprise Guide, SAS Enterprise Miner, SAS JMP, SPSS Modeler, R, STATGraphics, Matlab, Mathematica (Wolfram), Tableau, Spot fire, Data Flux

Programming Languages: C, C++,Java, Python, SQL and SAS.

Database: Teradata, Microsoft SQL Server, MySQL, Oracle, MS Access, PostgreSQL.

Productivity: MS Office (Power Point, Outlook, Project, Excel, Access).

Operating Systems: Windows, UNIX/ LINUX

PROFESSIONAL EXPERIENCE

Confidential, NJ

Data Scientist

Responsibilities:

• Conceptualized the platform governance and scorecard factors of front-end leasing application and risk business guidelines, thereby increasing productivity, skills, and consistency within the local area process for credit adjudication, contract terms, and conditions.
• Provided TEMPeffectual oversight to all credit adjudication resources, which involved personnel, systems, and scorecards. Presided over the entire risk procedures effecting the overall governance and risks within the platform, in relation with processing and activation of lease contracts.
• Use SQL skills to perform ETL for Teradata databases and created data sets, perform transformations on variables, model creation, validation and optimization through scoring.
• Extracted data from the database using SAS/Access, SAS/SQL procedures to create datasets
• Conducted multivariate segmentation analysis, data modeling, performance analysis and forecasting using RStudio and SAS
• Utilized SAS Enterprise Miner for market mix modeling, segmentation, and market basket analysis and clustering techniques to produce monthly and quarterly reports
• Generated plots and used the visualization tools through R and RStudio Programming
• Conducted analysis to resolve business issues and assisted in preparing firm communication materials for internal and external audiences. Examples include: risk issues, vendor negotiations, and senior management presentations.
• Reviewed market data to verify integrity and consistency for completeness, accuracy and suitability and implemented business logics to solve the performance issues
• Retrieved the data from flat files received from the vendors and converted to SAS data sets using DDE functions for analysis using SAS/STAT procedures such as PROC MEANS, PROC SUMMARY, PROC REG, PROC UNIVARIATE and PROC ANOVA
• Extensively read different forms of Input files like CSV and other formatted files using infile and Proc Import and documented using SAS scripting to develop data cleansing operationsx
• Scripted SAS programs with the use of Base SAS and SAS/MACROS for transferring and converting data (character to numeric and numeric to character) from Excel files to another to be used for further analysis and created global and local variables
• Created reports using analysis output and exported them to the web to enable the customers to have access through internet using SCL
• Gathered both business and technical requirements from both formal and informal sessions. Performed gap analysis and checked compatibility of existing system infrastructure with the new business requirements and translated these requirements into use cases. Extracted, cleaned, validated and, analyzed, report data from various sources, including databases, manual files and external websites.

Environment: SAS Enterprise Guide 5.1,SAS 9.3, SAS/BASE, SAS/BI, SAS/Graph, SAS/Stat, SAS/SQL, SAS/ODS, Excel, R,R Studio, Oracle 10g/11g, Windows NT, UNIX, Teradata, DB2.

Confidential, NJ

Data Scientist

Responsibilities:

• Financial data from the database is extracted using SAS/Access, SAS SQL, SAS/Connect, and Procedure and create SAS permanent data sets in SAS library.
• Creating SAS Views from tables in Database using SAS/Access, and analyze data.
• Write the SAS code and run those data sets to produce necessary financial reports by using SAS/STAT Procedures such as PROC Freq, PROC Tabulate, PROC Univariate, and PROC ANOVA.
• Design of ETL process to meet the requirement of data demand.
• Retrieved the financial data from flat files received from the vendors, convert them into SAS readable format. Make the SAS data sets, analyze data as per given requirement.
• Writing Meta data for important data set before archive into SAS metadata server.
• Extensively used procedures like PROC SQL, PROC PRINT, and PROC SORT etc. Used data
• Cleaning tools such as Proc Freq, Proc Print, Data null, Proc means, Proc tabulate, Proc Univariate, Proc SQL.
• Created required financial reports using analysis output and export them to other environments or the web using various SAS method like create delimited, text files, CPORT, ODS having formats such as HTML, RTF, or XML.
• Regular interaction with the financial analysts for the presentation.
• Performed in-depth quantitative data analysis.
• Coded SAS programs with the use of Base SAS and SAS/Macros for ad hoc jobs.
• Experience in Advance SQL to extract data from various databases like Oracle.
• Experience in Transferring and converting data from one platform to another to be used for further analysis. (From Oracle and Excel to SAS and vice versa)
• Interfaced programs with Oracle databases to provide accurate reporting, archiving, and error handling.
• Created required financial reports using analysis output and export them to other environments or the web using various SASODS methods for creating delimited text files, HTML, RTF, or XML files.
• Regular interaction with the financial analysts for the presentation.
• Performed in-depth quantitative data analysis.
• Extensively used procedures like PROC SQL, PROC PRINT, and PROC SORT etc.
• Coded SAS programs with the use of Base SAS and SAS/Macros for ad hoc jobs.
• Experience in Advance SQL to extract data from various databases like Oracle.

Environment: Base SAS, SAS/Access, SAS/Connect, SAS/Stat, SAS/Graph, SAS/SQL, SAS/ODS, SAS/Macros, SAS/ETL, UNIX SAS, PC SAS,SQL,MySQL Oracle 9i, DB2, PL/SQL, MS Excel, MS Access, Korn Shell

Confidential, WI

Data Scientist

Responsibilities:

• Collaborate with physicians, medical writers and data managers to finalize mock tables
• Design; select appropriate SAS procedures for each statistical analysis; test-run SAS program on mock data to ensure smooth analysis implementation.
• Use PROC SQL/IMPORT to import data from mainframe oracle clinical databases and MS excel sheets. Perform Data analysis, statistical analysis, generated reports, listings and graphs using SAS Tools SAS/Base, SAS/Macro and SAS/Graph, SAS/SQL, SAS/Access.
• Produce quality customized reports by using PROC TABULATE, PROC RPORT Styles, and ODS RTF and also provide descriptive statistics using PROC MEANS, PROC FREQ, and PROC UNIVARIATE.
• Work with statistician to analyze the results obtained from various statistical procedures like Chi-Square, PROC ANOVA, GLM, and T-test.
• Develop and debug routine SAS macros to create tables, graphs and listings.
• Provide proper validation, including testing and documentation (e.g., requirements document, program validation), in accordance with GCP and company standards.
• Contribute to the development of manuscripts, labels, scientific and commercial presentations, and regulatory response documents by generating statistical tables and graphs through SAS programming.

Environment: SAS/BASE, SAS/MACROS, SAS/SQL,SQL,PL/SQL, ODS RTF, SAS/STAT, SAS ETL, SAS/Enterprise Guide, SAS/Grid, SAS Data Integration, Excel, Windows, SPSS, Oracle, Teradata.

Confidential, PA

Market Data Scientist

Responsibilities:

• Revenue assurance and reporting department using internal system tools like PC SAS, SAS EG, and UNIX on TARO server, and TOAD for oracle, TERADATA SQL Assistance, WIN SCP and SAS Mainframe.
• Specially involved in Marketing team - Production area with NDW (National Data Warehouse) and TERADATA.
• Was closely working with Business Intelligence team for setting up new assignment, pulling data, making new processes, maintain and documents them by using SAS BI tools.
• Worked with and reported to executive directors to provide business requirements/reports by pulling data from TARADATA database, ORACLE database (TOAD), very large dataset by using PC SAS and SAS EG.
• Created complex SQL query by using specifies TERADATA specific SQL with PROC SQL (EXPLICIT - SQL pass through) and using LIBNAME statement (SAS SQL - IMPLICIT) on TERADATA as well as on UNIX SAS server.
• Debug, Create, maintain and documented AD HOCS reports on demands.
• Created SAS data sets by extracting data from Oracle database and flat files using Proc SQL, Proc Import, SAS Data Step, cleaned, validated and manipulated data by SAS and SQL.
• Created report using report wizard with an OLAP Cube, using templates with an information map, also created OLAP Cube with SAS OLAP Cube studio, also did work on SAS Add-In for MS with SAS BI team.
• Supported, troubleshoots, and maintained production systems as required, resolving problems, and providing timely follow-up on identified issues.
• Created reports including tables, listings, and Graphs by using PROC TABULATE, PROC SUMMARY, PROC FREQ, PROC REPORT, and PROC GPLOT.
• Use Data null to create date logic by using macros.
• Use PROC CONTENTS to change the variable name by creating MACROS.
• Created DDE and templates based on SAS code by using MACROS, select and put options for final output.
• Exported and imported data from or in to SAS environment by using wizard and PROC EXPORT/IMPORT statements.
• Scheduled job on CRON for daily, weekly and monthly SAS processes for automation, also rescheduled, dropped and delete SAS processes by using UNIX commands.
• Work on data space management by maintaining datasets created by SAS automation processes by using UNIX CONSOL command.
• Attended annually, monthly and daily meetings in order to set up new goals like customer loyalty program, Customer segmentation, and new product launch.
• Use RSA and CISCO system to connect remote computer and submit SAS code and DDEs remotely on PC SAS.
• Handled datasets has more than 800 variables and millions of observations.

Environment: SAS 9.2, 9.3, SAS Enterprise Guide 4.2/4.3, UNIX TARO server, TOAD for Oracle, SAS WRS, CRON-facility for SAS automation and WIN SCP- for Data sharing.

Confidential

Data Scientist

Responsibilities:

• Extracted data from Oracle using SQL Pass through facility, Proc Access, Libname Method and generated ad-hoc reports.
• Transferring and migrating data from Oracle to SAS datasets to be used for further statistical analysis.
• Primary Statistical analysis is done using Matlab, R.
• Responsible for creating new code, utilize existing code and maintain data in SAS.
• Created SAS datasets from raw data files with different field structures using trailing and in the data step.
• Built summary reports after identifying the customers, their occupancy period and the revenue generated using PROC SUMMARY, PROC MEANS and PROC FREQ.
• Used SAS system macros for error handling, code validation, date stamping of log files, collected files to a given directory and scheduling.
• Performed data analysis, data migration, data preparation, graphical presentation, statistical analysis, reporting, validation and documentation.

Environment: Windows XP, Matlab, R, SAS 9.2, SAS/Macro, PostgreSQL SAS/ODS, MySQL, SAS/SQL, SAS/STAT, Excel, PROC SQL, PC SAS, ORACLE.