SUMMARY

• SAS Programmer/Data Scientist expert with professional experience of working on different statistical tools, software and techniques for Stochastic Modeling, Statistical Analysis, and Data Mining in Text Analytics(NLP), Consumer Lending (Credit Cards, Mortgages) and Market Research.
• 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.
• Good Knowledge of Capital Markets and Structured Finance (MBS, ABS, RMBS, CDO, CDS, CMO, Swaps).
• Strong Statistical Skills: Linear/Nonlinear Regression, GLM, Logistic Regression, Multivariate Analysis, Time Series Model (ARIMA, GARCH, ARCH), Survival Analysis, Factorial Analysis, PCA, Non-parametric Analysis, Discriminate Analysis, Bayesian Statistics.
• Expertise in automation of SAS code performance optimization, models and reports using SAS tools.
• Experience in data preparation for various statistical modeling, which includes data cleansing, descriptive statistics, missing data analysis, data validation and preliminary data reporting using SPSS modeler and SAS.
• High-level experience in Base SAS, SAS/MACROS, SAS/SQL, SAS/STAT, SAS/CONNECT, SAS/ACCESS, SAS/GRAPH, SAS/ODS, SAS/OLAP, SAS/EBI, SAS/ETL, SAS/GRID, SAS/ETS, SAS Visualizer, and SPSS Modeler.
• Adept in Base SAS, SAS/MACROS, SAS/SQL, SAS/GRAPH, SAS/ACCESS, SAS/STAT, SAS/IntrNet, SAS/CONNECT and SAS/ODS etc. in Windows & UNIX environment.
• Experience in data analysis and processing using machine learning algorithms
• Adept in semantic text analysis on music-related databases using Natural Language Processing (NLP) techniques
• Data scraping (Web and third-party APIs), cleansing and parsing of heterogeneous datasets
• 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.
• Experience using statistical language such as R, Matlab, and Mathematica for developing and documenting quant models.
• Experience with IML (Interactive matrix programming with integration to R)
• 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.
• 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.

TECHNICAL SKILLS

Statistical: SPSS Modeler, R, R Studio, Weka,, Python, STAT Graphics, Matlab, Mathematica (Wolfram), Tableau, Spot fire, Data Flux

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

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

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

Operating Systems: Windows, UNIX/ LINUX

SAS Skill Set: SAS Base 9.3 +, SAS/STAT, SAS/GRAPH, SAS/CONNECT, SAS Enterprise Guide 5.1, SAS Data Integration Studio 4.3 +, SAS Web Report Studio 4.3, SAS Information Map Studio 4.3, SAS BI suite, SAS OLAP Cube Studio 4.3, SAS Access engine, SAS 9.3 Grid computing, SAS Scalable Performance Data Server (SPDS), SAS Enterprise Miner 7.1

PROFESSIONAL EXPERIENCE

Sr. SAS Consultant

Confidential, New Jersey

Responsibilities:

• Responsible for model development for estimation of credit risk and automation of the credit analysis process in the firm.
• Developed different models in SAS for various financial products present in the firm:
• Credit Risk model to assess default probability and score credit insurance clients.
• Quantitative model for Asset Based Lending (ABL) cash flows projections.
• Model to determine percentage of outstanding invoice to be funded in a Receivables Financing.
• Model to analyze need of Credit AR puts and swaps for firms.
• Model to assess the effect of macro level risk factors on a firm: Political Risk Protection, a product to protect international operations in case of a macro-level political event.
• Developed analytics algorithms in R scripts for FGI TRUST Program - a credit insurance tool for proactively monitoring insurance policies and ensuring collection on all claims.
• Performed ad hoc model development specific for quantitative analysis of credit risk using SAS.
• Used ANOVA analysis, decision trees and regression techniques.
• Generated plots and used the visualization tools through R and R-Studio Programming.
• Set methods and procedures for model estimation, validation and data requirements.
• Worked with risk, finance and other business units to explain statistical models, their meaning and implications.
• Documented methodology, data reports and model results and communicated with Project Team/Manager to share the knowledge.
• Worked on advance querying the databases using SAS in calculating and computing columns, using filters, manipulated and prepared the data for reporting and statistical summarization.

Environment: SAS9.2, SAS/SQL, SAS EnterpriseGuide5.1, SAS/STAT, SAS/GRAPH, SAS/CONNECT, SAS Enterprise Guide 5.1, SAS Data Integration Studio 4.3, SAS BI suite, SAS OLAP Cube Studio 4.3, SAS Access engine, SAS 9.3 SAS/Connect, SAS/Access, SAS/STAT, SAS/Graph, R, VBA in Excel, Tableau, Oracle Database.

SAS Quantitative Consultant / Programmer

Confidential, New York

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

SAS Programmer

Confidential, Wisconsin

Responsibilities:

• Reviewed the Business Requirement Documents and the Functional Specification.
• Extracted data from the database using SAS/Access, SAS/SQL procedures and created SAS data sets for statistical analysis, validation and documentation.
• Used procedures such as Proc Freq, Proc Means, Proc Sort, Proc Print, Proc Tabulate and Proc Report.
• Modified and developed macros for report generation using SAS/MACROS as per the statistician requirements.
• Developed SAS programs for statistical analyses and data displays.
• Performed data analysis, statistical analysis, generated reports, listings and graphs using SAS.
• Extracted raw data from an Oracle database and used SAS/ACCESS to read it and run statistical analysis using SAS/Stat.
• Involved in modifying Legacy Data Warehouse SAS jobs to run on the MDW platform and execute SQL against the DB2.
• Executed the SAS jobs in batch mode through UNIX shell scripts.
• Worked on advance querying of the database using SAS Enterprise Guide for calculating and computing columns by using filters.
• Manipulated and prepared the data for reporting and statistical summarization.
• Involved in designing the project and process flow diagrams using SAS Enterprise Guide.
• Conducted data mining and statistical analysis using R (t-test, Chi-Square test, ANOVA, and logistic regression) to improve existing strategies.
• Executed design, coding, testing, debugging, and documentation of multiple treatment and payment SAS programs for charge-off card data.
• Involved in Physical modeling on Teradata such as creation of tables, indexes and views.
• Analyzed existing SAS scripts based on various platforms such as UNIX, Windows and Mainframe.
• Prepared daily, monthly, and ad hoc reports (by PowerPoint, Excel, pivot tables, and pivot charts, etc.), and present findings and recommendations to all levels of senior management.
• Develop SAS macros for automating the analysis, process, and report generation.
• Wrote SAS reports to Excel, the SAS content server, HTML, and PDF.
• Automated SAS jobs running on a daily, weekly and monthly basis using SAS/BI and Unix Shell Scripting
• Review and modify SAS Programs, created customized ad-hoc reports, process data for publishing business reports; automate and distribute designed business reports on schedule in various format.
• Created SAS Macros and SAS Graphics. Customize the existing programs using macros as per the statistician's requirements
• Generated SAS customized reports using the DATA NULL and Proc Report techniques.

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

Market Data Scientist

Confidential, Pennsylvania

Responsibilities:

• Worked as a SAS programmer and analyst in 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, SAS Base 9.3 +, SAS/STAT, SAS/GRAPH, SAS/CONNECT, SAS Enterprise Guide 5.1, SAS Data Integration Studio 4.3 +, SAS Web Report Studio 4.3, SAS Information Map Studio 4.3, SAS BI suite, SAS OLAP Cube Studio 4.3, SAS Access engine, UNIX TARO server, TOAD for Oracle, SAS WRS, CRON-facility for SAS automation and WIN SCP- for Data sharing.

SAS Programmer

Confidential

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, SAS Base 9.3 +, SAS/STAT, SAS/GRAPH, SAS/CONNECT, SAS Enterprise Guide 5.1, SAS Data Integration Studio 4.3,SAS BI suite, PostgreSQL SAS/ODS, MySQL, SAS/SQL, SAS/STAT, Excel, PROC SQL, PC SAS, ORACLE.