TECHNICAL SKILLS

• Software: SAS v9.2 and v 9.3, SAS/BASE, SAS/STAT, SAS/GRAPH, SAS/MACROS, SAS /ODS, SAS ENTERPRISE MINER, SAS ENTERPRISE GUIDE, SAS VISUAL ANALYTICS, SUDAAN, R, WEKA, MICROSOFT AZURE MACHINE LEARNING STUDIO, SPLUS, SPSS, XML, TERADATA, TERADATA STUDIO, APACHE HADOOP, PIG, HIVE, YARN, PYTHON, SCALA, HORTON WORKS, AWS, AMBARI, APACHE SPARK, APACHE MAHOUT, PYSPARK, SPARKR, MAP REDUCE, CPLEX, TABLEAU,SCALA, JIRA, PUTTY, MOBAXTERM, TOAD, RATTLE, INTERSYTEMS DEEPSEE, INTERSYSTEMS HEALTHSHARE, INTERSYSTEMS CACHE, PENTAHO, SYNEDIT, CRISP - DM, MINITAB, VISUAL BASIC, MS SQL 2012, MS VISIO, DBMS COPY, ORACLE, EPI-INFO, ENDNOTE, PUBMED, WORD, ACCESS, EXCEL AND CRYSTAL REPORTS.
• Operating Systems: Windows XP, Windows 7, Windows 8, and UNIX

PROFESSIONAL EXPERIENCE

Confidential, Duluth, GA

Senior Data Scientist

Responsibilities:

• Provide Data Science, Machine Learning, Predictive Analytics expertise using MS Azure Machine Learning Studio to create Predictive Models that predict Customer Transit Days for Customized Tranist Lanes.
• Utilize Azure Machine learning R, Python, SQL modules to aid with data manipulation, data restructuring and data cleaning.
• Work Collaboratively with the Data Management team to understand customer requirements utilized in the Training and Predictive Models.
• Test Predictive Models for Performance and Accuracy using MS Azure Web Services
• Utilize CPLEX for Model Prototyping
• Utilize Cross Industry Standard Process for Data Mining (CRISP-DM) methodology for Data Science Projects; Business Understanding, Data Understanding, Data Preparation, Modeling, Evaluation and Deployment

Confidential, Duluth, GA

Senior Data Scientist/Informatics Scientist

Responsibilities:

• Provide Data Science, Machine Learning, Predictive Analytics expertise using R, Python, IBM Watson Cognitive and Watson Analytics Tool to guide the Drug Development process for a Personalized Medicine Use Case Using Real World Evidence (RWE) Data; Explorys and Truven Health Claims Data
• Utilize CPLEX for Model Prototyping
• Utilize Cross Industry Standard Process for Data Mining (CRISP- DM) methodology for Data Science Projects; Business Understanding, Data Understanding, Data Preparation, Modeling, Evaluation and Deployment
• Create Data Visualizations and Dashboards using Tableau.
• Provide Data Science, Predictive Analytics and Big Data expertise to Verizon, Inc. supporting their Financial Management sector to help mitigate Churn; Involuntary and Voluntary Churn and Bad Debt Using Machine Learning Algorithms.
• Apply Time Series Forecasting Models to generation predictions
• Work with Developers in the Creation of a Data Lake; Create Views, Target tables and Unit Test tables.
• Provide Informatics and Data Science expertise to create Predictive Models to predict probabalities for different disease cost/utilization using Claims Data to Aid in Decision Making ; Supporting the Revenue/Pricing Department.
• Generate Propensity scores for Multivariate Predictive Statistical Models using SAS Enterprise Miner; Logistic Regression
• Perform Model Remediation for different Statistical Models; Emergency Room, Total Knee, Obesity and Hip Replacement models.
• Apply Machine Learning Techniques to Clinical Data using Python, SPSS, SAS and R; Supervised Learning and Unsupervised Learning.
• Apply Machine Learning Algorithms; Random Forest, Decision Trees; C4.5 & CART; Self Organizing Maps-Neural Networks and K-Means for Customer Segmentation in Marketing Campaigns.
• Utilize Episode Treatment Group (ETG) ; Symmetry 7/9, ICD-9 and ICD-10 data to gauge Model Stability due to certain data elements changing.
• Create SQL code using the MySQL and Teradata SQL Assistant Tool to Query and Create Tables.
• Provide Business Requirements Gathering expertise for Internal and External clients to understand Client problems and needs.
• Support the Marketing Department with their Data Science and Statistical Needs For Steerage Campaigns for different member groups such as Steerage towards Patient Centered Medical Home (PCMH).
• Created Data Visualizations using TABLEAU and SAS Visual Analytics.
• Participate in Software Development Life Cycle processes to guide developers in customizing applications to meet Client Enterprise Analytical Needs.

Confidential, Duluth, GA

Senior Data Scientist/Informatics Expert

Responsibilities:

• Provide Data Science, Predictive Analytics and Big Data expertise to Verizon, Inc. supporting their Financial Management sector to help mitigate Churn; Involuntary and Voluntary Churn and Bad Debt.
• Provide Subject Matter Expertise in Statistical Modeling-Predictive Analytics/Modeling for a Congestive Heart Failure Patients (CHF) Cohort using Electronic Health Record (EHR) data from EPIC and GE Centricity EHRs and Claims Data.
• Utilize CPLEX for Model Prototyping
• Use R and SAS to perform Statistical Modeling/Predictive Models - Time Series/Forecasting for Emergency Room Clinical Data using Predictive Modeling MarkUp Language (PMML).
• Apply Machine Learning Techniques to Clinical and Environmental data using SAS, R WEKA, Python, SPSS; Supervised Learning and Unsupervised Learning .
• Use APACHE HADOOP to perform Distributed Processing of Large Clinical datasets.
• Use R, SAS, Python, and SPSS to Implement Mathematical Algorithms for Clinical Data; Decision Trees, Random Forest, Support Vector Machine (SVM), K-Means and K-nearest neighbors; k-NN.
• Use SAS ETL to Extract, Transform and Load Clinical and Claims Data.
• Use R, SAS and SPSS to create Calculated/Derived Variables for Clinical and Claims Data .
• Use PROC SQL and SQL language to perform Data Queries.
• Create the Design of a Stroke Diagnostic Clinical Decision Support System with the following major components: Mobile technology, Knowledge base, Bayesian Network-NaiVe Bayes Algorithmns, Machine Learning, Computer Algorithms, Data Warehouse and Rules Engine.
• Provide FDA Regulatory and Compliance expertise to a Phase III Clinical Trials for an Osteoporosis study.
• Provide Informatics expertise to ensure 21 CFR Part 11 compliance for all SQL databases, SAS Programs, and SAS datasets .
• Provide CDISC Standards/Programming expertise for clinical trials data; SDTM, ADaM, Controlled Terminology, ODM, Define-XML.
• Write SAS Programs to perform data management, cleaning, create tables, listings, graphs and used SAS Macros for clinical trials data.
• Use SAS to analyze repeated measures clinical data using the General Estimating Equations method (GEE), applying Quasi-likelihood methods and using Score and Wald Statistics.
• Serve as a Subject Matter Expert on gathering system requirements and Use Case Analysis for a hospital based Health Care Associated Infection (HAI) Smart Tool System that aids with Centers For Disease Control- Confidential /NHSN Reporting.
• Provide Medical Informatics expertise in standard vocabularies such as LO INC, SNOMED, HL7, ICD-9, ICD-10, Healthcare Service Location, and RxNorm for HAI Smart Tool.
• Act as a liaison between Information Technology (IT) and the Medical professionals during the design phase of the HAI Smart Tool.
• Use MS Visio to create Workflow diagrams and Information Data Models.
• Provide expertise in HL7 Clinical Document Architecture (CDA) implementation including identifying technical barriers during implementation process.

Confidential, Atlanta, GA

Senior Statistician

Responsibilities:

• Provided Statistical and Programming support to Confidential National Health Studies; BRFSS, STEPS and ASTHMA Studies.
• Performed Sampling and Weighting of the Behavioral Risk Surveillance Study (BRFSS)/STEPS to a healthier U.S.A data and the Asthma States Project data.
• Provided training (6/5/2007) to 35 U.S states on Weighting for the Asthma data. 100 participants on a teleconference.
• Applied means imputation of age and race to the BRFSS/STEPS data.
• Calculation of post-stratification factors and adjustment factors (inverse of probability of selection.)
• Wrote SAS callable SUDAAN programs to perform Statistical analysis: Logistic Regression and Linear Regression.
• Wrote SAS Macros Programs to perform data management and data cleaning.
• Generation of reports using SAS/ODS to produce RTF, HTML, PDF, XML and EXCEL formats.
• Wrote SAS Programs that convert SAS datasets to SPSS files.
• Performed edit checks on the SPSS files using SPSS to ensure data quality.
• Provided consultation on Statistical methodology to include Multi-variable regression analysis, Trend analysis, Multi-collinearity, effective model building, sample size and power calculations.
• Provided consultation on longitudinal data analysis to include Proc mixed, Proc Multi-log, Proc Genmod, and appropriate correlation matrixes.
• Reviewed Asthma Research Protocols to understand the sampling and selection criteria-- probability of selection for the Asthma follow-up subjects, thus apply a weighting method to calculate the correct adjustment factors.

Confidential, Atlanta, GA iSdiS Programmer

Responsibilities:

• Wrote SAS edit/check programs for Youth Risk Behavior Study (YRBS) data to check percentages, frequencies, indicator variables, and missing values.
• Created SAS datasets from ASCII Files for the  as part of the number checking process.
• Wrote SAS/SUDAAN programs to calculate the confidence intervals for the YRBS 2001 data as a validation measure for the Morbidity and Mortality Weekly Report (MMWR).
• Performed descriptive statistical analysis using SPSS on the YRBS 1990­2001 data as an edit/check measure on the SPSS files.
• Wrote SAS/SUDAAN program using SAS Macros for the YRBS 2001 dataset. The SAS/SUDAAN Program calculates the confidence intervals for age, grade, and race for all the local states using SUDAAN’s Proc Descript.
• Used Visual Basic to configure the YRBS questionnaires, verify and validate the edit criteria for the YRBS 2001 Michigan Alternative Schools.
• Created SAS datasets and formatted SAS libraries for the Principal and Teachers Study (PROFILES) 2002 and used SAS edit checks to clean data and minimize data errors.