SUMMARY

• Over 7 years of experience in various areas including econometric analysis, risk modeling, data analysis, data analytics, data mining, data modeling, reporting, financial analysis and web technologies in highly quantitative environments in banking, insurance, retail and healthcare services industries.
• Unique blend of education and experience, tailored for highly quantitative multidisciplinary roles with banking and financial firms.
• Expert in SAS programming, data processing, data collection, quantitative and qualitative data analysis and reporting.
• Experience in analysis, design, development, implementation and maintenance of complex quantitative models using SAS.
• Experience in extracting/creating, merging, analyzing and reporting large SAS datasets of up to 22 million records.
• Experience in developing and modifying SAS Programs and Macros for data extraction, data integration, data cleaning, validation, and query writing and reporting.
• Good understanding and hands - on experience on Econometric and Statistical analysis such as Correlation Analysis, Hypothesis testing, ANOVA, Multivariate Statistical Analysis, Linear & Non-linear Regression Analysis.
• Good understanding and hands-on experience on Forecasting Techniques such as BASS model, Survival Analysis and Time Series Analysis(ARIMA); Factor Reduction Techniques such as Principal Components, Factor Analysis and Conjoint analysis.
• Expert in conducting Segmentation techniques such as Cluster Analysis(Hierarchical & Non-Hierarchical), Decile Analysis and RFM Analysis, and Response Analysis techniques such as Discriminant Analysis and Logit Model.
• Good understanding and hands-on experience on Risk Analytics such as Probability of Default (PD), Loss Given Default (LGD) and Exposure at Default (EAD).
• Have rich experience in implementing Customer Analytics Models for Discrete-Time Duration Data, Continuous-Time Duration Data, Count Data and Choice Data.
• Experience in CRM Marketing, Campaign management and promotion analytics and Modeling tools including Eviews, SPSS and MATLAB.
• Knowledge and experience in using SAS Products like SAS DI Studio, SAS Enterprise Guide and SAS Enterprise Miner.
• Experience in Base SAS, Advanced SAS, Unix SAS SAS/SQL, SAS/MACROS, SAS/ODS, SAS/STAT, SAS ETL.
• Solid understanding and proficient use of various procedures like proc SQL, proc report, proc freq, proc means, proc contents, proc dataset, proc append, proc import, proc export, proc univariate, proc print and proc sort
• Excellent use of formats and informats, which includes building of new formats using proc format/value statement.
• 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.
• Strong experience in coding using SQL, Procedures/Functions and SAS macros.
• Extensive experience in preparation of reports, tables, listings and graphs using various platforms like MS Excel, SAS EG, SAS EM, Tableau and Crystal Reports.
• Good at creating, reviewing, retrieving, validating datasets and to read, write, import and export to another data file formats.
• Knowledge in data warehousing and business intelligence concepts.
• A strong set of quantitative and analytical skills demonstrated through advanced academic training and extensive practical experiences.
• Proven ability to lead and motivate people, possess excellent organizational, time management, communication and presentation skills.

TECHNICAL SKILLS

Quantitative Financial Analysis: Financial Statements, Investment & Portfolio, Asset Pricing and Econometrics

Data Analytics & Statistical Analysis: SAS, SPSS, SAS Enterprise Miner, SAS Enterprise Guide, R, Eviews, EXCEL Modeling and MATLAB

Advanced Programming: SAS, C, SQL, SDLC using 6-sigma principles

SAS Products SAS 9.X and SAS 8.X: SAS/BASE, SAS/STAT, SAS/EG, SAS/MACRO, SAS/SQL, SAS/GRAPH, SAS/ODS, SAS/BI, SAS/DI-STUDIO, SAS/ACCESS, SAS/EIS, SAS/AF and Data Mart

Databases & Operation Systems: Oracle, PL/SQL, Netezza, Teradata,UNIX and PC WINDOWS.

Reporting & Visualization: SAP BW, SAP BI/BO, Tableau, Crystal Reports

Other skills: Data Warehousing, Web Technologies, Unix Shell Scripting and Microsoft Office

PROFESSIONAL EXPERIENCE

Confidential, Richmond, VA

Sr SAS Consultant

Responsibilities:

• Used mathematical, analytical, and econometric tools to provide ongoing analysis of new and existing products, asset classes, portfolios and suggested relevant portfolio management actions as necessary.
• Performed loss forecast analysis and reporting as well as ongoing ad hoc model development and analysis for specific clients needing high level quantitative analysis of credit risk, product valuation and asset analysis.
• Played a key role in the development of credit default index that measured the balance-weighted proportion of consumer credit accounts that go into default each month.
• CreatedSASdata sets by extracting data from Oracle database and flat files using PROC SQL, PROC Import,and SAS Data Step.
• Conducted statistical analyses using linear and nonlinear regressions (PROC REG and PROC NLIN), logistic regression (PROC Logistic), and general linear models (PROC GLM).
• Created reports including tables, listings, and graphs by using PROC TABULATE, PROC SUMMARY, PROC FREQ, PROC REPORT, and PROC GPLOT.
• Collaborated with teams in planning and structuring transactions to assist in credit analysis and pricing.
• Performed high-level quantitative credit risk analysis with the internal and external data.
• Validated SAS datasets using SAS procedures like PROC Means, PROC Frequency, PROC Univariate, and PROC Rank.
• Extensively used SAS procedures such as PROC APPEND, PROC IMPORT, PROC SUMMARY, PROC CONTENTS, PROC SurveySelect, PROC Transpose and PROC SQL.
• Used SAS DATA NULL and PUT statements to create the customized reports
• Development of macros to provide transformation variables from a single input variable.
• Search for meaningful patterns, trends, and relationships by sifting through large amounts of data.
• Wrote advanced financial engineering programs using SAS and UNIX.
• Developed several SAS analytics models and reports using SAS/EG.
• Used PROC SQL for ad-hoc report programming, to perform the tasks like data manipulation of multiple views in Oracle, creation of the ad hoc reports for marketing research data, preplanning and doing ad hoc joining of multiple Oracle views.
• Designed and developed several SAS reports for budgeting, Activity-Based costing and other financial planning processes.
• Developed Data Mart views for presentation of the management reports.

Environment: SAS V9.2, SAS/BASE, SAS/STAT, SAS/MACROS, SAS/BI, SAS/GRAPH, SAS/SQL, SAS/ODS, SAS/EG 4.1, and Data Marts.

Confidential, San Francisco, CA

Sr SAS Programmer/Analyst

Responsibilities:

• Responsible for Data Extraction, Data Preparation, Data Validation and Analysis.
• Extensively used SAS Enterprise Guide for data validation and performing data investigation.
• Built SAS models to support critical business problems such as which bundled software components customers use the most, which video cards to support, how many customers are finding and using new product features.
• Work with the Data Analytics Program Manager in implementing a comprehensive Data Analytics (DA) Program including DA process, tools, etc.
• Drive DA Activities within the global Finance team and Corporate business process owners including: identifying, designing, deploying, documenting and performing analytics to provide additional risk and controls insights.
• Interact with the business users to understand the issues/requirements
• Work with project leads to develop and perform data analysis procedures as applicable in support of ongoing projects especially in automating compliance activities for the business.
• Used Enterprise Miner to conduct Segmentation Analysis on the target market to identify the existing trend and to create a profile of the same.
• Worked on income and demographic data sets to identify consumer segments.
• Conducted regression analysis to decide which factors are statistically significant in deciding the propensity to buy a product from each segment.
• Involved in data mining and data modelling using Base SAS for customer retention and modeling churn.
• Developed insights and recommendations based on model outputs.
• CreatedSASdata sets by extracting data from Teradata and flat files using PROC SQL, PROC Import,and SAS Data Step
• Develop and deploy an automated reporting platform that is used to provide internal and external customer insights to enable retention and up sell efforts within 12 months.
• Run at least 8 reporting insights experiments per year to provide unique insights on customer engagement & rate plan performance to enable the development of predictive analytics that can be used to drive continuous customer value.
• Summarized customers according to product type, amount spent and lifetime value (LTV) measures.
• Used Base SAS procedures FREQ, SQL, SORT, TABULATE, and MEANS to analyze the data
• Created RTF, PDF and HTML Reports using SAS ODS, and ODS TRACE statement to the log file.
• Generated the HTML embedded links to SAS graphs and reports formatting the output for the web browsers.
• Prepared several ad-hoc reports using macros according to statistician’s specifications.

Environment: Base SAS, SAS/SQL, SAS/Graphs, SAS/Stat, SAS/Access, SAS Enterprise Miner, SAS Enterprise Guide, Oracle, MS Access, VBA, Windows XP.

Confidential, Charlotte, NC

SAS Analyst

Responsibilities:

• Utilized both financial analysis and programming skills in a multidisciplinary role which involved data modeling, econometric analysis, risk modeling and data analytics using SAS, SPSS and spreadsheet modeling Excel .
• Developed Credit Risk Analytics models such as Probability of Default (PD), Loss Given Default (LGD) and Exposure at Default (EAD).
• Played a key role in data analysis and data modeling model design, development, and model implementation, using SAS, SPSS & EXCEL of the innovative products of ScoreLogix.
• Ensured that the models are maintained and updated in a timely manner to meet the expected performance.
• Developed insights and recommendations based on model outputs.
• Extracted data from the large database of size up to 7 million records using SAS/Access, SAS SQL procedures and created SAS datasets.
• Retrieved the econometric data from flat files, oracle database and converted to SAS data sets for analysis using SAS/STAT procedures.
• Developed SAS programs extensively using Base SAS, SAS/EG and SAS/Macros.
• Demonstrated high level of competency in statistical and analytical principles, tools and techniques and supported the advancement of the “best-in-class” analytical capabilities.
• Acted as a liaison among decision sciences, business technology teams and other business partners across the organization.
• Managed a modeling team in the U.S. and coordinated with an offshore development team in India to provide modeling support for decision sciences functions.
• Played a key role in business development activities such as sales presentations and conferences.
• Developed and maintained the ScoreLogix database for 6 different products, with datasets drilled down at the zip code level for all the 50 US states.

Environment: SAS V9.2, SAS/BASE, SAS/STAT, SAS/MACROS, SAS/GRAPH, SAS/SQL, SAS/ODS, SAS/ACCESS, SAS/EG 4.2, and SAS/CONNECT

Confidential, Atlanta, GA

SAS Programmer/Business Analyst

Responsibilities:

• Build customer segmentation model to define the types of Confidential customers.
• Designed trigger campaign for CRM team where a customer will receive a reminder email to purchase replacement products like air filter and water filter.
• Build regression model to identify customers who may be remodeling their restroom, living room or kitchen and other repairs around the house.
• Performed Market Basket Analysis or Attachment Analysis.
• Performed Decile Analysis of customers every month to see the shift in customer deciles.
• Created a random sample from the extracted dataset to decide on the control group and pilot group.
• Performed statistical analysis and data management on study data by utilizing appropriate statistical methods using SAS and SAS tools.
• Integrated the results of Marketing Mix Analysis, Price Elasticity and other advanced analyses into business planning process.
• Developed insights and recommendations based on model outputs and present it to the business users.
• Support the management to drive the adoption of the analytics insights among the business users
• Send out coupons to the customer based on online browsing behavior.
• Utilized my experience with Unix Shell Scripting to create shell scripts for batch running of SAS programs.
• Extracted, performed validation and generated SAS data sets from Netezza by applying SQL Pass through Facility.
• Having experience with ODS output and ODS TAGSETS.
• Performed transformations like Merge, Sort and Update to get the data in required format.
• Strong knowledge of database environments like Oracle, DB2, Teradata and Netezza.
• Having experience in the SQL tools like Rapid SQL, Toad and SQL Developer.
• Used Winscp & SFTP to transfer EXCEL AND CSV format files from UNIX environment to windows.

Environment: SAS, BASE/SAS, SAS/MACRO, SAS/SQL, SAS/CONNECT, SAS/ACCESS, SAS/ODS, Oracle 11g, Sybase, DB2, UNIX and Windows 2003/XP.

Confidential, Salt Lake City, Utah

SAS Programmer/Business Analyst

Responsibilities:

• Collaborate with physicians, medical writers and data managers to finalize mock tables.
• Design and 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.
• Derive analysis datasets such as AE, CM, DS, DM, VS, TV, MH combined with CDISC SDTM Standards with the techniques of Macro, SQL Join, and DATA Step Sort and Merge.
• 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, REPORT, and SUMMARY 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 PROC ANOVA, GLM, and T-test.
• Develop and debug routine SAS macros to create tables, graphs and listings.
• Contribute to Integrated Summary of Safety Analysis Datasets and Reports (TLF - Tables, Listings and Figures) for clinical studies.
• 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, SAS/STAT, SAS ETL, SAS/EG, Excel, Windows, Oracle.

Confidential

SAS Analytics Consultant

Responsibilities:

• Maintained mainframes performance reports and created reports for online and batch applications for various servers. Created charts showing mainframe performance using SAS/GRAPH.
• Coordinated the production of monthly, quarterly and annual performance reports for senior management.
• Modified data using SAS/BASE & Macros, performed statistical analysis of the data using SAS and prepared graphs using the modified data for business analysis.
• Created several datasets on the Remote Server. Extracted data sets from mainframe server using PROC CIMPORT and created datasets in SAS libraries.
• Developed SAS programs with the use of SAS/BASE and SAS/Macros for ad hoc jobs.
• Executed SAS scripts on mainframes and the exported the output datasets into SAS.
• Maintained and enhanced existing SAS reporting programs for marketing campaigns.
• Executed reporting programs and download the results into EXCEL and built pivot tables for further analysis and presented the statistical reports for the marketing department.
• Moved datasets across platforms from PC and Mainframe to UNIX and vice versa.
• Involved in extracting, analyzing and auditing marketing data from the data-warehouse using SAS.
• Participated in marketing campaign-planning meetings with program managers in order to develop and document campaigns specifications.
• Created SAS data sets by extracting data from Oracle tables using SAS/CONNECT and SAS/ACCESS.
• Generated SAS/ MACROS and several PL/SQL stored procedures for reusability and to minimize data processing.
• Developed scripts, procedures and applications to generate sophisticated ad hoc reports using SAS/EIS and SAS/AF.
• Wrote large aggregation SQL queries using in-line views.

Environment: SAS V8.2, SAS/BASE, SAS/STAT, SAS/MACROS, SAS/GRAPH, SAS/SQL, SAS/ODS, SAS/CONNECT and SAS/ACCESS