SUMMARY:

• 7+ years of Experienced Senior Advanced SAS Programmer and Analytics Statistical Modeler with extensive experience in building and/or supporting models in banking/finance, retail, insurance and entertainment industries.
• Data preparation for various statistical modelling, which includes data cleansing, descriptive statistics, missing data analysis, data validation and preliminary data reporting.
• Highly proficient in interactive matrix language (IML) in SAS.
• Worked on FICO Blaze Advisor to make business rules for smarter decisions.
• Highly proficient in SAS/Base,SAS/STAT, SAS/GRAPH,SAS/CONNECT, SAS/Macros, SAS/SQL, SAS/Access, SAS Enterprise Guide, SAS Access engine, SAS Grid computing, SAS Scalable Performance Data Server (SPDS), SAS Enterprise Miner.
• Experienced in SAS Data Integration Studio, SAS Web Report Studio, SAS Information Map Studio, SAS BI suite, SAS OLAP Cube Studio.
• Expertise in building Analytical and Statistical Models for database marketing, risk management groups.
• Strong expertise in analytical and quantitative techniques including predictive modeling and multivariate analysis.
• Extensive work experience in slicing and dicing big data using advanced techniques like SAS multiprocessing, SAS pipeline parallelism, SAS indexes, SAS views.
• Sound statistical knowledge to infer valid conclusions from volumes of data.
• Extensive experience in preparation of reports, tables, listing and graphs.
• Proficiency in Time Series and Forecasting techniques using SAS Enterprise Miner.
• Strong knowledge in Classification models and advanced statistical and mathematical modelling techniques.
• Expertise in automation of SAS processes, models and reports using SAS tools.
• Extensive experience in using RDBMS, Oracle, MySQL, Teradata.
• Experience in quantitative analysis and research, data mining, aggregation and validation, model development, scoring and validation of predictive models including financial time series models using SAS.
• Have experience in doing excellent documentation on business requirements
• Strong experience with databases like Oracle 9i/8i, MS SQL Server 2008, DB2, and MS Access.
• Extensive experience to handle Large Teradata for Data Cleansing, Data Profiling and Data Scrubbing.
• Involved in coding and pulling data from various oracle tables using Unions and Joins.
• Calculate the one - way frequencies, multi-way frequencies for counts of variables and table analysis using PROC FREQ with LIST, OUT, MISSING options.
• Customize the variables to user-defined Formats using PROC FORMAT in printing reports.
• Generate custom reports with line sizes, page breaks, Header message, Bottom message using PROC SORT, PROC PRINT, PROC REPORT.
• Extensive knowledge of advanced SAS/STAT procedures including Multivariate Analysis, Regression, ANOVA, Graph and Plot
• Experience in developing and maintaining user interface using HTML, XML.
• Expertise in using various SAS report generating procedures like PROC REPORT, PROC SQL, PROC FREQ, PROC MEANS, PROC TABULATE, PROC TRANSPOSE and PROC PRINT
• 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
• Possess a strong ability to adapt and learn new technologies and new business lines rapidly
• Effective team player with strong communication & interpersonal skills.
• Writes and runs complex SQL scripts on ODBC, Netezza and Teradata database servers to extract records on terabyte and petabyte scale for analysis and modeling.
• 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
• Conducts coding of qualitative variables and manipulation, complex hypothesis testing and statistical analysis through various statistical methodologies like experimental designs (ANOVA with or without replication, factorial design, ANCOVA etc), MANOVA, discriminant and factor analysis and statistical inferences in SAS.

TECHNICAL SKILLS:

Statistical software: Base SAS, SAS/SQL, SAS/Macros, SAS/ODS, SAS/CONNECT, SAS Enterprise Miner, SAS Enterprise Guide, Interactive Matrix Language (IML)

Languages: SAS, SQL, Python, R

Tools: FICO Blaze Advisor, XML, SQL Advantage, Tableau, Qlikview, Vb-scripting, Microstrategy, Cognos, WinSCP, Putty

Databases: MS Access, DB2, Microsoft SQL Server, Teradata, Oracle

Software Packages: Microsoft Office 2010 (word, Excel, PowerPoint)

PROFESSIONAL EXPERIENCE:

Confidential, NYC

SAS Modeler/Programmer

Responsibilities:

• Designing, developing, testing, deploying, and maintaining analytic applications and data structures needed for modeling and forecasting
• Leveraging efficient coding techniques to optimize / improve performance
• Implement statistical, economic, econometric or other mathematical models for Chase’s CCAR team (consumer bank )
• Use the built-in operators and the functions in the SAS/IML for matrix operations
• Create novel graphs using SAS/ IML that cannot be created by SAS/GRAPH
• Use SAS Access engine, SAS 9.3 Grid computing, SAS Scalable Performance Data Server (SPDS) to access for processing large volumes of data on the server
• Fit the explanatory models and investigate multivariate relations using SAS?IML
• Work with Enterprise Data Warehouse (ICDW) staff members to map variables from their source systems to tables and data sets used by the modeling team and to create necessary meta data to document sources and field definitions
• Responsible for all aspects of data management for the modeling team
• Assist modeling team members with questions surrounding sources of data files and definitions of data fields
• Process analysis and process improvement
• Creating technical and user documentation
• Identifying innovative techniques and/or developing utilities that increase the speed and efficiency of the modeling tool set
• SAS programming to maintain and develop advanced SAS coding techniques to write maximum efficient and performance optimized code
• Apply and demonstrate expertise with efficient DATA step, SQL programming, SAS Macro programming and SAS Array processing
• Maintaining data and code from different development environments (development to test to production)
• Efficiently handling and managing massive volumes of data (large SAS Datasets with upwards of tens of millions of records and/or terabytes of data storage)
• Use Unix operating system with Korn shell scripting
• Lead and/or actively participate in SAS knowledge-sharing activities
• Understand existing coding and processing to troubleshoot and resolved issues as they arise

Confidential

SAS Predictive Modeler /SAS Programmer

Responsibilities:

• Big Data Mining for customer acquisition and customer retention
• Create predictive models based on 200,000,000+ grocery store Point of Sale data to target new customer and reduce customer defection using SAS Enterprise Miner
• Participate in design and implementation of Data Mining procedures for both new predictive modeling techniques and improvements in processing efficiencies
• Provide complete solutions to business problems using data analysis, data mining techniques and statistics like chi square, correlation, logistic regression and decision tree technique
• Use SAS Access engine, SAS 9.3 Grid computing, SAS Scalable Performance Data Server (SPDS) to access for processing large volumes of data on the server
• Construct modules in SAS/IML to pass arguments to R
• Call the functions in R using SAS/IML
• Transfer data to and from the SAS?IML and the R Interface
• Score full database of 200,000,000+ IDs using the desired predictor variables
• Improved redemption rate of Data Mining print programs by 3% -4% or $700,000 on average
• Communicate details of models and projects to the Sales and clients

Confidential

SAS Modeler/Programmer

Responsibilities:

• Collaborated with multiple departments for their analytical needs in multiproduct environment in areas such as Database Marketing, Segmented Pricing and Attrition Prediction.
• Create predictive models using logistic regression or decision trees in SAS Enterprise Miner
• Developing frame works in collaboration with Statisticians, Business teams and Programmers for strategic and tactical needs through experimental designs.
• Design high quality business rules system applications through FICO Blaze Advisor and solutions to improve control over operational decisions.
• Extracted data from different sources (Primary and Secondary), used tools like Oracle and Teradata and text files using SAS/Access, SAS SQL procedures and created SAS datasets.
• Performed data preparation and transformation using SAS procedures to ensure data quality and consistency.
• Used XML to express the relationships between forms and use this information to control both the user interface and a validating application
• Used Mathematical Markup Language, MathML, from XML to embed mathematical and scientific equations in Web pagess
• Developed SAS programs to create a customer mailing list for Direct Mailing and Telemarketing.
• Extensive Experience in writing shell scripts for executing SAS batch files on UNIX environment to save the execution time and for automation.
• Created SAS database files, Ad-hoc analyses and graphical reports, developed standard reports and supported SAS users. Involved in extracting, analyzing and clustering marketing data (according to customer demographic profile).
• Used SAS PROC SQL to extract data from different relational database management (Teradata) systems.
• Imported Data from relational database (ORACLE) into SAS files per detailed specifications.
• Imported data using LIBNAME and PROC SQL Pass -Thru facility to reduce processing time.
• Performed complex statistical analysis using PROC MEANS, PROC FREQ, PROC UNIVARIATE, PROC REG, and PROC ANOVA.
• Developed, modified, and generated Daily Wells Owned Ownership and Monthly Wells Owned Loan Level reports having 50+ Million records data querying from Oracle using SQL Pass-thru summarizing business activity and created financial data sets using DATA steps and DATA NULL .
• Read datasets with a lot of missing values using MISSOVER and TRUNCOVER.
• Interacted with data using the Dynamic Data Exchange (DDE) facility in SAS.
• 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 reports in the style format (RTF, PDF and HTML) using ODS statements and PROC TEMPLATE
• Effectively prepared and published various performance reports and presentations
• Develop Ad-hoc report using SAS Enterprise Guide.
• 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.
• 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.
• Maintained and enhanced existing SAS reporting programs for marketing campaigns.
• Conducted significance tests and study response rates for different offers.

Confidential

SAS Programmer /Modeler

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.
• Prepared audit statistics on providers and policyholders using various fraud detection techniques.
• Generated reports and analysed on aggregate claims statistics.
• Developed predictive models to detect anomalies in claims.
• Extracted data from different sources like claims data mart and text files using SAS/Access, SAS SQL 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.

Confidential

SAS Pricing Strategy Analyst/Modeler

Responsibilities:

• Conduct and interpret macro and micro pricing modeling and scenarios, evaluate post pricing analytics for item pricing across categories and price zones along with detailed analysis to determine current and projected profitability
• Generate advance level analysis and reports to estimate the impact of price changes on the items sales, volumes and profitability
• Collaborate with the Pricing Strategy and Analytics Manager in making product pricing change recommendations to merchant leadership teams
• Provide analytical pricing support by preparing to merchants and planning teams
• Write and understand SQL queries to mine the data and identify trends

Confidential, Chicago IL

Statistical Analyst/Modeler

Responsibilities:

• Collecting internal and external data for segmentation development, testing, roll out, and performance monitoring

  Developing consumer segmentation framework, via predictive modeling (eg. K-means, factor analysis)

• Application of other relevant analytical procedures with the ultimate goal of identifying -unique consumer segments with respect to business objectives
• Partner with business stakeholders to develop appropriate strategy for each consumer segment based on their value, demographics, needs/attitudes, and other relevant characteristics
• Improving Aetnas holistic understanding of consumers and members in order to continue enhancing our ability to provide proper products, services, and engage consumers leveraging an array of media assets
• Applying off the shelf segmentation product with internal data, including internally developed segments, apply it to successfully solve business problems, implement, and measure success
• Provide performance monitoring for each segment based on marketing performance, product performance, user experience, and other applicable KPIs