SUMMARY:

• Base SAS (Data Step, Macro Facility, Base Procedures).
• SAS/SQL (to extract information from Oracle, TERADATA, DB2, and Sybase).
• SAS Enterprise Guide (SAS EBI client).
• Dynamic SAS Macro code.
• Effective SAS processing of large data sets (200 million records).
• Operating Systems: UNIX and Windows.
• Working knowledge in SAS Connect (for remote session processing and data transfer in a client server environment).
• Working knowledge in SAS EBI multi - tier architecture and tool suite.
• Working knowledge in data warehousing and ETL processing.
• Data retrieval, data manipulation, macro programming, custom-reporting, and the computation of key business metrics (in SAS).
• Problem resolution and SAS enterprise application upgrades.
• Research, analysis, and resolution of user-specified questions (related to enterprise SAS applications).
• Application lifecycle management procedures and version control software.

PROFESSIONAL EXPERIENCE:

Confidential

Consultant

Responsibilities:

• Performed a significant software upgrade of an existing enterprise application that functioned to compute and report statistical measures of performance across a series of mortgage risk models. The purpose of the upgrade was to enable model performance monitoring that was comprehensive of those forecasts related to default, liquidation, and prepayment. Code modification and unit-testing contributed to a new release of the application software (as part of a CCAR initiative). The work was performed using SAS, version 9.3, in a Unix-based, development environment. Tools and skills emphasized Base SAS, SAS Data Step, SAS Macro Language, Base SAS Procedures, SAS Output Delivery System, and SAS Connect. Source data consisted of loan-level detail on credit risk drivers and loan performance (actual and forecast) for a given cohort and mortgage-related portfolio in each month of the observation window.

Confidential

Consultant

Responsibilities:

• Provided quality assurance with regard to the conversion of financial information in the upgrade of a posting and billing system related to consumer credit cards. SAS Enterprise Guide was used on a UNIX platform to construct SAS programs and SAS SQL queries that functioned to extract, join, transform, and compare test data that originated in the pre-conversion and post-conversion schemata. Test data included information from DB2 tables at the account, offer, balance, and transaction levels. Comparative test results were documented in Excel, and defects were tracked using application lifecycle management tools. Specific s included the provision of source code to implement complex transformations and the identification of numerous defects in the post-conversion pricing of promotional offers.

Confidential, Columbia, MD

Consultant

Responsibilities:

• SAS (version 9.1.3) was utilized in a UNIX environment to perform significant modification and upgrade to an existing production application as related to the Physician Quality Reporting program under CMS. New and updated government requirements were implemented in the current program year while innovation was provided to improve both method and accuracy in achieving the required program results. Such results consisted of summary statistics in a series of client reports that tracked progress in quality data submissions (through a web interface) by Medicare Part B service provider groups. Client reports were
• Developed in SAS and delivered in Microsoft Excel via email attachment. Quality data was sourced from Oracle and included beneficiary samples representing a series of disease modules and Confidential t care measures. The following software tools were utilized: Base SAS, SAS Data Step, SAS Macro, SAS Procedures, SAS SQL, SAS Output Delivery System, SAS SQL Pass Through, UNIX scripts, and version control software. Application lifecycle management procedures were followed through deployment to production.

Confidential

Consultant

Responsibilities:

• Ongoing problem resolution was provided with regard to an enterprise software application that was critical in the support of a claims payment operation for high-cost Confidential ts in the stop-loss insurance industry. Worked directly with business customers to analyze and solve problems, leading to change requests and the implementation of upgrades as part of enterprise application releases. Written explanatory summaries were provided regarding the research, analysis, and resolution of problems that were user-identified. Problem-solving success rate was one hundred percent. Enterprise application programs were run on a
• UNIX server in a production environment and were written in Base SAS, SAS Macro, SAS SQL, and UNIX scripts (drivers). Numerous programs and modules comprised both batch and ad hoc (reporting) components of the system. Data was sourced from a corporate warehouse (TERADATA) including medical claims and enrollment information and from an Oracle database including stop-loss insurance policy-related information.

Confidential, Washington D.C

Consultant

Responsibilities:

• Designed and built an analytical dataset to support time trend analysis of prices in the non-performing loan portfolio. The dataset was built and augmented through the development of a series of programs (in Base SAS, SAS Macro, and SAS SQL under Windows) to perform monthly ETL processing according to specification and business rules. Source data was extracted and integrated from multiple systems, including a predictive pricing model and a dealer survey. Transformation included data aggregation across loan dimensions, computation of UPB weighted average prices, ranking of property state by UPB, and match-merging of results as summarized across multiple dimensions and sources of input data. Subsequent to transformation, the monthly, aggregate, and integral data was loaded to a (permanent) target repository in SAS. Subsequent to data load, additional manipulation in SAS included data transposition and export to Excel for the production of graphs that compared aggregate model and dealer prices across time and loan dimensions (such as unpaid principal balance, loan-to-value ratio, months delinquent, property state, and modification type).

Confidential, Rockville, MD

Consultant

Responsibilities:

• Designed and built an analytical dataset to support the analysis of financial and operational risk for member firms within industry segment. The dataset was built and augmented through the development of a series of programs (in Base SAS Version 9.1.3, SAS Macro, SAS SQL, and SAS Enterprise Guide) running on a UNIX server to perform quarterly ETL processing according to specification and business rules. Source data was extracted and integrated from numerous relational tables comprising an enterprise Oracle database. Subsequent to extraction, data transformation included numerous table joins to correctly relate member firms, quarterly SEC filing events, and detailed financial information contained within those filings (income, assets, liabilities, net capital, and reserves). Computations included financial risk measures, percentiles within industry segment, relative risk scores based on percentiles within industry segment, and overall rank based on risk within industry segment. The resulting statistical profiles of financial and operational risk were loaded to a (permanent) target repository in SAS. Subsequent to data load, results were exported from SAS to Excel for distribution to end users and were utilized to identify high-risk, high-impact member firms for onsite audits.

Confidential, Washington DC

Consultant

Responsibilities:

• SAS support services were carried out (in a SAS EBI environment) with regard to existing production programs that were run on a scheduled basis to track and report resources related to the USCG Deepwater acquisition and modernization program. For example, SAS programming was performed to explore data in enterprise Oracle relational tables that represented accounts and transactions. Subsequent to data exploration in Oracle, there was an upgrade to an existing production program so as to access and accommodate the enterprise Oracle data in improving the quality and timeliness of reporting with regard to financial obligations and expenditures related to Deepwater. Production programs utilized Base SAS (Version 9.1), SAS Macro, SAS SQL, SAS Output Delivery System (ODS), and SAS Connect to perform data extraction, data manipulation, and the generation of HTML documents and multi-dimensional cubes that were uploaded from a database server to a SAS EBI Information Delivery Portal on a Web server. In another example, SAS programs were developed to extract, verify, transform, and load monthly data from archived text files to historical repositories in SAS that were the basis for readiness reporting across surface, aviation, people, and positions.

Confidential, Bethesda, MD

Consultant

Responsibilities:

• Used Base SAS (Version 9.1) on a Windows XP platform to carry out tasks that included both ad hoc programming and the new development of production reports to support the business areas of risk management, finance, and trading. Specific s included the development of programs to generate flagship risk reports that are run daily to measure compliance in the areas of securities portfolio size, age, and exposure to market risk factors. End-user reports were developed in SAS, exported to MS
• Excel, and formatted using Dynamic Data Exchange (DDE). Also worked with existing source code to acquire knowledge of current processes so as to modify, maintain, and improve those processes. For example, SAS programs extracted current-day portfolio snapshots from multiple flat files and subsequently transformed, manipulated, and loaded such data to permanent historical repositories in SAS. Historical repositories were the basis for daily, weekly, and monthly enterprise reporting.

Confidential, McLean, VA

Consultant

Responsibilities:

• Reverse engineering was performed with regard to a series of Base SAS programs comprising a monthly process used to track and report on inventory activity related to REO properties. Reverse engineering entailed a comprehensive review of existing source code comprising the current process and the preparation of documents describing the technical and functional aspects of that process. The detailed documentation of the current process was used as a basis for determining requirements in the rewrite and upgrade of that process.

Confidential, Dulles, VA

Consultant

Responsibilities:

• Used Base SAS and SAS SQL (Version 8) on a Unix platform to rewrite a series of programs that comprised an e-commerce daily production system for the processing of online merchandising transactions, revenue, and costs (associated with orders submitted, cancelled, shipped, and returned). The programs were rewritten to improve system performance through conversion from SYBASE stored procedures to SAS. Unit testing and quality control was performed on the new system. System output in the form of database tables (SYBASE) serve as the basis for financial analysis, projections, and reporting related to AOL online shopping.

Confidential, Washington D.C

Consultant

Responsibilities:

• Used Base SAS (Version 8) on a Windows XP platform to create programs for the import of health care cost data from survey responses stored in Excel. For each of two cost surveys, multiple SAS Macro programs were created and executed for each survey respondent to undergo processing from Excel to SAS across provider cost data, provider benefits data, site-specific cost data, and regional cost data (programs utilized Import and Export procedures as well as DDE). In addition to the program software, deliverables included SAS data files, hardcopy test prints, and a series of hardcopy exception reports. In addition, SAS programming was performed to support the statistical analysis of total wages and hours reported by staff category in each of several health care cost surveys.

Confidential, Washington D.C

Consultant

Responsibilities:

• Used Base SAS (Version 8) on a Windows NT platform to create, verify, analyze, and report on tax data for the support of revenue estimation and economic research. The data were from a variety of sources including: weighted samples of individual, corporate, and tax-exempt returns; sale of capital assets data (SOCA); the individual return match file (including forms W2 and 1099);and estate tax returns of decedents that were part of a 1040 panel.
• Deliverables included verified SAS data files that resulted from the development of programs to read large tax data files in ASCII format that consisted of millions of records and multiple tax forms spanning several compact discs. Provided a series of detailed, customized, hard-copy reports that resulted from the development of source code to process W-2 forms in payee/payer groups; merge individual tax returns to W-2 forms by primary, secondary, and dependent social security numbers; and update existing W-2 forms to in corporate amendments. Ad hoc programming was performed to satisfy ongoing requests.