PROFESSIONAL SUMMARY:

• Data Scientist with Over 15 years of experience in data analytics, and design of analytic systems for teh Healthcare, Financial, Direct Marketing, Insurance and Pharmaceutical industries.
• Published author and recognized thought leader in business analytics, Data Architecture, Predictive Modeling, Data Science and Data Analytics, Statistical Analysis, using SAS, R, Tableau, Spark, and Excel

WORK EXPERIENCE:

Confidential

Data Architect/Data Scientist

Responsibilities:

• Developed risk scoring models for current and prospective customers utilizing demographic, operation, and Pharmacy data. Definition of 20 standardized cohorts with test and control groups, and analysis of disease matrices.
• Development of Medicare AgeIn Predictive Models to product chase lists which target members who may be at risk to move from commercial to competitors Medicare Advantage Plan.
• Churn prediction
• Innovate for teh future: Proposals/Proof - of-concepts for various prototype data science analytical projects: Re-admission likelihood, missing HCC’s, and churn reasons/survival analysis.
• Data Architecture and Analytics, Visualization, ETL coding, and Trend analysis for a Health Insurance based Actuarial BI Data Warehouse. Implemented business solutions involving member enrollment/retention, claims, reserving, and health care utililization. Line of Business Segmentation, loss triangles preparation. New affordable Care (ACA) product analysis. Analysis of Revenue Neutrality of ICD9-ICD10 Diagnosis Code Migration.
• Management of Agile (Scrum) Projects for internal team and external consultants. Issued recommendations for Data Governance. Modeled and advocated for best practices throughout teh organization. Partners with Marketing, Financial, Underwriting, and Pharmacy on various strategic projects involving quick and accurate delivery of insightful analytics.
• Held Leadership role on various committees (including SAS User Group, and BI Governance) for promoting best practices in analytics, data warehousing, and team building.

Cognizant Technologies

BI Architect

Responsibilities:

• Dashboarding, visualization, Predictive Modeling, Decision Trees (CART, CHAID), Logistic Regression, and Cluster Analysis using software from SAS Institute and Tableau Software. Text Mining and Classification of customer comments using software from Clarabridge and Megaputer(PolyAnalyst Text Miner).
• Development of Logistic Models which predicted propensity of customer to be a detractor or promoter (NPS or RTF Scale). Evaluation of Champion vs. Challenger models. Principal Component analytics of structured and unstructured variables to include within model.

Confidential

Sr. Analyst

Responsibilities:

• Definition and Development of Analytical Processes and Use Cases for IT property and Casualty department.
• Application of advanced Data Mining and Predictive Modeling techniques to Healthcare, Auto, and Fast Food business lines (Cluster analysis, Decision Trees, etc.)
• Documented and presented analytical results to Senior Management
• Forecasting of loan reserves using SAS and R
• Implemented SSIS Procedures to collect data from various sources including: External data feeds using FTP, XML, and CSV connectors, and internal tables and Excel spreadsheets. In addition to standard merging and joining of disparate data, utilized “fuzzy match”, and term extraction transforms for data mining.
• Implemented analytical cube structures using SSAS with up to 10 dimensions with partitions spanning 10 years of monthly data. Teh data was browsed via Excel Pivot tables which were connected to teh SSAS server.

Independent consultant

Confidential

Responsibilities:

• Performed data analysis of historical customer files to identify predictive models. These models included prediction of repeat buyers, and incremental sales generated by email promotions. Segmentation projects included segmentation of Internet vs. Non-Internet catalog buyers, and responders vs. non-responders. Resolution of data integrity issues, and integration of data with over 50 complex internal Excel files. Profiled high, mid, and low value customers.
• Time Series forecasting of product demand
• Development of Home Price Indexing Database system IT procedures which extracted estimates of home values from external vendors files and integrated teh data into internal mortgage and home equity data.
• Predicted Credit Default Risk using Oracle Data Miner
• Conversion of an external vendor Marketing Campaign Tracking System to a new In-House SAS based tracking system saving teh company approximately $15,000 per month in vendor fees.
• Anti-Money-Laundering (AML) project for teh legal IT department of a major NYC financial institution. Detection of unusual wire transfer activity, transaction history not consistent with prior history, etc. Modified various ETL procedures to achieve results.
• Developed reports which helped management evaluate teh effectiveness of various marketing campaigns. Tests of significance of treatments vs. control groups, sample size determination, and reporting. Utilized SAS modeling tools to project data base growth, capacity, and utilization needs for 5 years forward.
• Interfaced SAS Programs with Business Objects and Unica Model One Data Mining Tools
• Developed Decision Support Systems which provided OLAP tools for teh analysis of revenue, usage, subscriber growth and retention (churn) of cellular subscribers. Development of specialized datamarts
• Development of a sales commission system using SAS which allowed implementation of various customizable commission plans, & allowed data entry & sales report tracking by various categories