SUMMARY:

• More than 5 years of experience with Analytics/Business Intelligence/SQL/Data Warehouse Testing/data modeling in the areas of pharmaceuticals and medical studies, finance, healthcare and insurance, database design and administration, programming, query - writing, and report development using analytics/BI tools
• More than 5 years of experience with statistical, visual, prescriptive and predictive analytics
• More than 5 years of experience in visualizing and telling the stories behind analytic scenarios (presenting to upper level management and Analytics conferences in Tableau, SAS, Powerpoint, Excel)
• More than 5 years of experience working with integrated teams creating reports to clarify possibilities and impacts, and present narrative analytics and data visualizations elucidating possible situations and scenarios
• More than 5 years of presenting monthly and weekly reports to upper level management and parallel teams covering operational planning, scenarios, budgets, trends and impacts
• Wide experience with analysis, query-writing and data structuring/ETL/Data Modeling in many varieties of SQL such as Impala, Teradata, Oracle (including PL/SQL), and SQL Server (T-SQL, SSIS, SSRS, SSAS)
• Expertise in analysis, development, hands-on coding and implementation of complete forecasting and analytic architectures using SAS (from SAS 82 to SAS 9.4), SAS Enterprise Guide, SAS MACROS, SAS PROC SQL, stored processes, hash functions, Python 2 and 3, SAS IML and SAS Statistical and Time series procedures in SASGRID and Hadoop structures and other (generally Linux-based) environments
• Leadership in developing scaled agile environments for financial models in SAS 9.4, Python, and R, with results expanded into visual structures (in Tableau, R, Python or SAS graphics) to narrate the data patterns and elucidate predicted or postulated situations and scenarios
• Mastery of predictive modeling, statistical analyses, back-testing of interrelated models, ongoing monitoring and evaluative data structuring in the operational, Enterprise and budget planning, marketing, macro-economic trend impacts, auditing and risk contexts
• Hands-on designing, coding, testing and implementation of predictive and prescriptive (mostly scenario-structured) models as well as extensive data visualization and Unit Acceptance Testing in Python, R, SAS and S-plus.
• Rebuilt, coded and implemented under DMF scheduling in production a streamlined set of Teradata routines for direct mail deposit expansion marketing campaigns replacing a SSIS/SSMS structure at Confidential .
• Developed, coded, tested and implemented a complete architecture for epidemiological studies using 3 million patients from the GPRD (the Data Mart for the health-care system of the UK) while at Confidential Health Solutions. This included all patient visits, drugs, treatments, events and outcomes and required extensive communication with epidemiological teams across the globe
• Confidential labelling for a common anti-depressant was changed as a result of this successful integration of complex treatment data, including timing of physician visits, drug treatments and behavioral outcomes
• Developed, coded, deployed, and provided ongoing monitoring and Unit Acceptance Testing of a set of critical risk logistic regression models for Business Intelligence related to wholesale risk scoring and Commercial Real Estate Loss Forecasting at Confidential . This coding for testing, automation, synchronization and implementation of logistic regression risk models, and Tableau and Latex output during the development and deployment of Hadoop/HIVE/Impala-based “productionized” segments of a SASGRID-based critical risk models. This included coding Python 3.5 with Pandas to parse data from Hadoop via the Pig JSONStorage function
• Presented at SAS Analytics Conference in Las Vegas, September 2016 on the use of Markov Chains in operational forecasting, and metabolic and prescriptive models
• Developed, coded, tested and implemented a complete forecasting architecture for all loan modification processing at Confidential . SAS 9.3 and 9.4, bash/LINUX scripts, SAS Enterprise Guide, SAS PROC SQL, SAS IML and SAS Statistical and Time series procedures were used to conduct predictive modeling of operational loan modification inventories and transitions for future periods of up to 3 years. This forecast was based on using matrices of stages in Markov Chain transition probability structures

WORK EXPERIENCE:

Analytic Consultant

Confidential

Responsibilities:

• Prototyping, testing and implementing new processes and automating data streams to analyze marketing campaigns for Small Business Deposits, Card Acquisition and Home Equity using SSIS (2014), SAS 9.4, Tableau and Teradata (15+) on Windows 10 and SASGRID on LINUX using SAS Enterprise Guide, SAS Studio, SAS on LINUX and Teradata assistant.
• Developing ETL procedures to support the above in a SASGRID/TERADATA sandbox environment (HEMISPHERE) for scheduled runs in the datamart framework.(DMF) on LINUX
• Improving the control and interactions for users on the “Regression Engine” - a set of applications that shows the impacts of different variables on the results of marketing campaigns - using Tableau, SAS EG, SAS macros, SAS prompts via EG and SAS procs such as LOGISTIC, REG and GLMSELECT and prompts from SAS EG.

Contract Technology Specialist

Confidential

Responsibilities:

• Automating health care service re-certification and review procedures using standard SAS macros, Data set (Base SAS 9.4 ), SAS add-in for MS Office, SAS Stored processes, SAS Enterprise Guide, SAS ODS RTF, Excel, VBA, VB, VBS and specialized SAS Procs
• Developing ETL from clinical and hospital reporting systems and reviewer commentaries
• Automating final, fully-formatted reporting documents in Word and Excel including letters, graphs and detailed supporting data, as well as dynamic and customizable reporting structures

Contract Technology Specialist

Confidential

Responsibilities:

• Used standard SAS macros, Data set (Base SAS), and specialized SAS Procs with Hadoop/HIVE/Impala to test the implementation (as well as Unit Acceptance Testing) of components of critical risk models and give preliminary BI interpretations of the effects of broad changes in methodology related to a Hadoop Data Warehouse
• Developed, hands-on coded, tested and implemented a complete BI architecture for evaluating data constructed from a range of sources
• Built and tested Latex and Tableau implementations to combine and assess Loss Forecasting models using logistic regression and monte carlo methods to expand the predictive range of structural models
• Coded Python 3.5 with Pandas to parse data from Hadoop via the Pig JSONStorage function
• Generally used SAS 9.4, UNIX, SASGRID, various forms of SQL (Impala, Teradata, Oracle, Proc SQL) and SAS Enterprise Guide in a Scaled Agile Framework as the basic query-writing environment for most of the above tasks
• Set up Epics in a scaled agile project environment to budget and guide development of very large Tableau arrays (and the Hadoop/HIVE/Impala views on which the arrays were based) describing a population stability indexing model as well as testing everything about population stability in an industrial sector and ensuring the dynamic reporting and customizability needed to access and use these arrays

Contract Analyst

Confidential

Responsibilities:

• Wrote SAS for bootstrapping, used proc surveyselect and hash functions
• Coded Shiny Pages and Monte Carlo models in R as well as bootstrapping in R
• Produced data visualization in R and SAS
• Developed and validated analytic processes to cut waste in Medicare programs
• Worked on Medicare Fraud detection
• Cross-checked procedures in R and SAS for accuracy and optimization in a DB2 SQL environment
• Controlled input and output using SAS intranet, ODS and ODS tagsets, Excel and R (with LATEX and Shiny or Tableau using JSON or XML in some cases)
• Ran simulations in R to ensure samples from large data are adequate to determine the 95% confidence interval for use in potential litigation
• Produced analyses in R (using Rstudio and statistical, graphics and input/output packages) and SAS 9.4 using large macros and statistical procs
• Wrote Unix scripts (bash and Bourne-shell) to automate testing

Analyst Consultant

Confidential

Responsibilities:

• Developed and implemented a complete forecasting architecture for all loan modification processing and operational budgeting at Confidential . SAS 9.3 and 9.4, SAS Enterprise Guide, SAS PROC SQL, SAS IML and SAS Statistical (including procedures for regression, logistic regression and multivariate autoregression) and Time series procedures were used to conduct predictive modeling of operational loan modification inventories and transitions for future periods of up to 3 years. This forecast was based on using matrices of stages in Markov Chain transition probability structures. Eventually this was migrated from a standard UNIX server to a SAS Grid analytic server. Integrated monthly systematic presentation of results to upper management into the system
• Inventories were predicted to within 1% even for periods beyond 6 months. This previously unheard-of level of accuracy was achieved within the first few months of implementation
• Code and procedural optimization during the initial phases of this project to automate and optimize reporting moved from EXCEL to SAS
• Presented analysis and recommendations to senior management, (in Excel, Tableau, PowerPoint and Word)
• Lead and coached programming teams to increase analytic accuracy using SAS
• Ensured adherence to data management regulations and policies. Worked with Data Governance teams to identify the sources, paths, modifications, summarization and definition of data elements used in forecasting and capacity planning in the loan modification space
• Applied the SAS value-added methodology to determine the cost-effectiveness and operational value of the forecast, and explaining and characterizing factors that drive the forecast such as population changes and other types of variability (not well-covered in the SAS value-added methodology)
• Used multiple databases and server structures such as SASGRID1 via SAS connect with UNIX-type methods, T-SQL on SSMS (with SSIS, SSRS and SSAS). Oracle PL/SQL and SAS Enterprise Guide
• Assessed needs and team skills for addressing new types of analyses and capabilities development such as using Tableau.

Contract Analyst

Confidential, Charlotte, NC

Responsibilities:

• Created model development and data analysis for all loan investors
• Worked with SAS, SQL, PL/SQL, SAS IML and SAS Statistical and Time Series Procs
• Oversaw the automation of Excel VB analyses into SAS analyses

Contract SAS Programmer

Confidential, Cary, North Carolina

Responsibilities:

• Designed and built Confidential /Clinical Data Consortium Compliant Study Databases for review by independent scientific agencies. This included all forms of analysis and data manipulation, from setting flags to building structures based on the interrelation of dates and times
• Worked with SAS Base, Macros and Oracle technologies to complete Study Databases with full audit trails and complete analytic variables
• Advised Statisticians on the consistency and implementation of study and database specifications based on my experience working with Data Monitoring Boards

Senior Statistical Analyst/Lead Programmer

Confidential, Research Triangle Park, NC

Responsibilities:

• Developed and implemented a complete architecture for epidemiological studies using 3 million patients from the GPRD (the health-care system of the UK) while at RTI Health Solutions. This included all patient visits, drugs, treatments, events and outcomes and required extensive communication with epidemiological teams across the globe.
• Confidential labelling for a common anti-depressant was changed as a result of this successful integration of complex treatment data, including timing of physician visits, drug treatments and behavioral outcomes
• Wrote Standard Operating Procedures (SOPs) for the range of types of studies. This required gathering and codifying study requirements and data specifications from clients, clinicians and statisticians. Developed full specs for all stages of analysis based on procedural outlines
• Worked with serious adverse event groups at RTI Health Solutions to bring their information out of their extremely rigid systems in a usable form. This included some unusual types of data extraction such as using SAS(JAVA) XMLmapper to read narratives
• Directed problem-solving with clients for the complex data problems that arise during programmatic transitions
• Conducted parallel validation of data, statistical and analytic results for clinical studies using stored processes in some cases
• Installed SAS 9.1.3 on a UNIX server at RTI Health Solutions and validated the installation to Confidential standards
• Worked with scientific advisory panels to reconstruct and programmatically replicate published studies from final data in order to demonstrate the completeness and accuracy of data in a research repository. This included an extraordinary range of data extraction and manipulation as well as SAS procs related to logistic regression and survival analyses such as PHreg.
• Prepared combined study data reports for Data Monitoring Boards. This included data extraction and modification of analyses from diverse studies
• Used S-plus, R and SAS for data visualization
• Prepared integrated drug safety data reports pulled from multiple studies for submission to the Confidential
• Created exploratory analyses of large databases (such as UNOS organ transplant data, cancer registries and insurance data) in collaboration with research statisticians and epidemiologists