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Data Architect Resume

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UtaH

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E  d  u  c  a  t  i  o  n
Mathematics Bachelor of Science, University of Utah; May 2005
E  x  p  e  r  i  e  n  c  e
Self-employedJan 2010 - Present

Confidential,
Layton, Utah                                                 May 2011 - Present

    1. Part-time academic instructor at a residential treatment center for boys.

 

Data Architect Confidential,
Salt Lake City, Utah                      Nov 2008 - Jan 2010

    1. Designed and created the ridership metrics system to collect, manage, analyze, and present ridership business intelligence for all modes of public transit from disparate data sources.
    2. Introduced SAS architecture (highly robust, scaleable, and sustainable), which was the engine of the ridership metrics system.
    3. Freed raw data sources through creating SAS programs which cleansed, ordered, and verified data into fact tables and summary tables.
    4. Fact and summary tables deployed for solid and efficient analysis meeting all analytic ridership needs through SAS. 
    5. Analytic results narrated by means of SAS graphics and reports which soundly articulated the story of what was happening with ridership. 
    6. Communicated to management architecture structure (Visio diagrams), proper data management protocols and methods, and provided tracking tools for progress of architecture creation.
    7. ETL (Extract, Transform, Load): data extraction, normalization, multidimensional data mart creation, and code writing for all necessary aspects of process, authored data dictionary.

 

Data Engineer, Confidential,
olumbia, South Carolina                                          Jan 2007 - Apr 2008
(Consultant through TM Floyd & Company an IT Consulting Group)

    1. Achieved and delivered nation wide analytics as a consultant to the Statistical Analysis Durable Medical Equipment Regional Carrier which provides services under contract to the Centers for Medicare & Medicaid Services (CMS). 
    2. Harnessed prodigious sized data sets containing confidential personal medical data, supplier data, and provider data, extracted from data sources ranging from raw claims data to summary file data marts, data intelligence was produced and maintained.
    3. Examples of data intelligence include standard monthly & quarterly reports, automated queries, trending analysis, fraud and abuse analysis, Freedom of Information Act reports, law enforcement requests (FBI, OIG, DOJ), ad hoc reports, and quarterly publications derived from individual research on consequential findings.  

Data Engineer, Confidential,
Salt Lake City, Utah                                           Jul 2005 - Jan 2007                     Regence Blue Cross of Utah (Noridian took over Medicare B Contract December 2005)

    1. Effectuated analysis for Medicare contractor by delivering descriptive and inferential analytics of confidential beneficiary and provider information. 
    2. Comprehensive analysis of data to identify and recognize trends and/or aberrancy\'s in provider practice patterns.  Created statistical and graphical ad-hoc reports from various data sources showing utilization profiles of providers and clinical groups. 
    3. Extracted, integrated and analyzed information from various data sources examples include modeling, linear regression, outlier identification, trending analysis, as well as inferential statistics of sampling, point estimates and confidence intervals. 
    4. Established and maintained baseline data in order to recognize unusual trends, changes in utilization over time.  Provided strategies that efficiently prevented or addressed systemic problems. 
    5. Documented the processes used in analysis and sampling.  Monitored the statistical program and recommend modification as needed.  Ensured that monthly and quarterly reports were produced and distributed timely and accurately. 

T o o l s  U s e d
SAS-Command advanced knowledge of SAS, SAS STAT, SAS GRAPH, SAS MACRO, SAS Enterprise Guide, SAS ODS, SAS/ACCESS, and PROC SQL. Create program code, reports, graphical aids, ETL process, importation and exportation of extremely large data sets. Essentially all heavy analysis and statistical techniques and research are performed using this architecture. Attended SUGI 31 (SAS Users Group International) conference in San Francisco at personal expense March 26-29, 2006.
SQL (Structured Query Language) - Use extensively.
Oracle: SQL Developer, and databases.
Microsoft: SQL Server, Word, Excel, Access, PowerPoint, Outlook, etc.
Other: Unix (AIX), IBM mainframe (JCL), DB2 relational database, Mac OS X (Pages, Numbers, Keynote), SPSS, and Maple.

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