SUMMARY

• Confidential earned a Ph.D. in Economics from Confidential University in 1996. He is looking to combine his prior experience with technology consulting in Confidential . He has experience across multiple industries including healthcare, consumer goods, retail, education, Government, E commerce, airline, and financial services.
• He is a proven Leader and Senior Data Scientist, Senior Economist using expert analytical skills to conduct robust analysis, enhance productivity and uncover additional revenue opportunities and loss forecasting by leveraging an enterprise big data.
• Demonstrated ability to interpret and summarize big data into meaningful information by using machine learning and artificial intelligence to create complex models from large databases.
• Possess advanced problem solving and conceptual thinking abilities with more than 19 years of professional experience in advanced analytics of great achievements.

TECHNICAL SKILLS

• SAS
• SPSS
• SQL for MVS Mainframe
• Unix and Windows Operating systems. JCL
• TSO
• Syncsort
• Microsoft Office. Databases: Access
• DB2
• Sybase
• Oracle

PROFESSIONAL EXPERIENCE

Confidential

Managing Consultant

Responsibilities:

• As a Managing Consultant for the U.S. Postal Service On Time Performance Model Project Description, I have built a robust model that predicted with great accuracy on time and late arrival international air carrier and propose alternative more efficient routes and constrained by lower prices.
• Trained and monitored Consultants on various statistical modeling techniques including regression, decision trees, forests and neural network within SAS enterprise minor.
• Ranked all airline lanes based on time performance and cost and then optimized international mail delivery.

Confidential | Miami, Florida

Director of Analytics

Responsibilities:

• Reporting to the Chief Marketing Officer, led the analytics team at Confidential .
• Hired, delegated tasks, motivated and evaluated the analytics team that exceeded the target in productivity.
• Built robust multi - channel attribution models that increased ad spent productivity on each TV and online by 35%
• Forecasted leads and sales across different products and thru different channels with great accuracy.
• Performed analytics that optimized the call center improving the leads conversion substantially.
• Scored leads using advanced algorithm that identified likely sales with great accuracy.
• Identified students segments that are likely to churn and made recommendations that reduced churn.
• Conducted advanced marketing mixed using econometrics models linear and nonlinear, stochastic and Bayesian
• Trained the team on SAS usage and served as the SAS software support to the team.

Confidential | Jacksonville, Florida

Senior Consultant

Responsibilities:

• Consulted for Other Party Liability and Medical Cost Management to detect fraud and discover additional savings.
• Used large claims ICD 9 data to predict claims that are not at fault auto accidents and worker’s compensation
• Identified millions of dollars in revenue that is undetected from auto accidents or worker’s compensation.
• Developed robust loss forecasting predictive models using neural network and various forms of data science.
• Wrote a SAS code that extracted, manipulated and transformed millions of records and close to a thousand variables before building the models.

Confidential, Fort Lauderdale, FL

Director of Research and Analytics

Responsibilities:

• Led and managed a team of senior researchers that performed advanced analytics across the university from academic to marketing, operation and admissions.
• Developed predictive models (regression, mixed moels, decision tree, neural network ) that calculated student lifetime value.
• Built robust time series forecasting models for enrollments and leads for each Department with great accuracy.
• Helped the University meet the accreditation requirements that ensures high quality of education that meets the requirement of the Higher Learning Commission by designing and evaluating a desired colloquium and pedagogy program and course outcomes.
• Collaborated with Deans, Department Chair, faculty and other administrators in designing and implementing the colloquia that improves the quality of education.
• Developed models for student retention/performance and faculty performance and strategies using data mining.
• Developed procedures for analyzing and documenting curricular metrics
• Developed insightful, creative, and end-user focused analytic solutions to questions of importance for one of the four academic verticals.
• Responsible for the collection, analysis, interpretation, distribution, and archiving of both business and academic data. The verticals Vice Presidents, Dean and Assistant Deans are the main clients and end-users of data.

Confidential, Miami FL

AVP/Senior Statistician

Responsibilities:

• Led and managed a team of senior analysts and an outside vendor that improved the customer insight, analyzed internal and external data for the largest prepaid telecom company.
• Reduced risk by forecasting with great accuracy activations, deactivations, reactivations and churn.
• Reduced churn and improved revenue significantly by developing advanced predictive models that made inference about customers who are likely to churn, take a promotion, buy airtime, or upgrade phone or plan.
• Collaborated with different department in executing promotional campaigns, designing product mix, pricing strategies and other analytics-based initiatives that reduced cost and increased revenue substantially.
• Created robust statistical models including decision tree, logistical regression, neural network and other pattern recognition technique using variables such as network coverage, technology (CDMA, GSM), handsets, customer’s service, and other customer touch points.
• Evaluated customers’ loyalty and win-back programs, customized offering
• Helped the client meet Sarbanes-Oxley act by estimating revenue generated from airtime used.

Confidential, Milwaukee, WI

Healthcare Statistician Manager

Responsibilities:

• Performed analytics that reduced the medical risk significantly.
• Applied statistical analyses (linear and nonlinear regression, logistical regression, decision tree, neural network and cluster analysis) that improved upon medical risk prediction and reduced cost by millions of dollars.
• Conducted the backdating study that detected potential fraud by agents in the field. This effort led to process improvement that reduced cost by reducing the cost-revenue ratio to less than 75%.
• Identified prospective large dollar claimants, thus pricing the policy accurately.
• Forecasted claim receipts by different lines of business, using time series applying AR, MA, ARIMA, state space and other models.
• Trained statisticians on different methods of forecasting who in turn improved the forecast accuracy.
• Leveraged internal data on healthcare policy member along with external big data for credit from Trans-Union and demographic data to identify profitable segments by applying data mining techniques Conducted micro simulation analyses that measured the elasticity of sales as price change. Conducted market and customer segmentation analyses that led to an increase in the revenue potential.
• Used trauma claims and ICD 9 data to predict fault auto accidents and worker’s compensation claims
• Wrote a SAS code that extracted, manipulated and transformed millions of records and close to a thousand variables before building the models.

Confidential, Dulles, VA

Principal Analyst

Responsibilities:

• Designed a robust statistical forecasting system that improved inventory and sales planning.
• As the project manager and the Principal analyst, led a team of analysts in developing a robust supply chain forecasting system for an inventory of more than a million SKUs that improved the forecast accuracy by 56%.
• Performed a system tests for QA, validation and mined large impression supply ad-server database and applied cluster analyses to optimize the forecasting system.
• Built analytics that improved upon the user's experience.
• Conducted performance-based analyses, mined large Sybase web data using several SAS products extensively in a UNIX environment Internet usage data that predicted users’ behavior for possible value-added opportunities that resulted in additional revenue potential.

Confidential | New York, NY

Senior consultant

Responsibilities:

• Designed market-segmented promotional campaigns for the data-marketing group for several DMAs, by mining a large and complex financial data that increased the response rate by 32%.
• Conducted credit score that reduced the risk exposure significantly
• Used large and complex financial, demographic and call center contact and collection data to develop predictive model that estimated the probability of getting the right party contact.
• Developed models that forecasted loss, calculated loss given default and probability of default (PD) and exposure at default.
• Created procedures for non-programmers to create reports automatically using SAS in an MVS environment.

Confidential, Washington, DC

Financial Economist

Responsibilities:

• Pioneered revenue initiatives that generated millions of dollars to the Confidential .
• The revenue initiative led to voluntary compliance in subsequent years leading to a budget surplus for the District.
• Performed analysis of economic and policy issues related to the tax base of the District of Columbia and estimation of potential tax revenue produced by the economy.
• Conducted several studies included: Who is Moving to and Who is Moving from the District of Columbia, Evidence from the Individual Income Tax Returns, A Commuter Tax for the Confidential: A Simulation; The Revenue Impact to the District of Columbia Resulting from the Closure of Pennsylvania Avenue near the White House, and The Tax Rate and Burden Shift Resulting from the Internal Revenue Service's Collection of Individual Income Taxes for the DC Government
• Incorporated contemporary, advanced statistical techniques as currently applied to the field of economics, statistics, finance, and policy analysis.
• Used and merged large data sets to create Statistics of Income publication. Forecasted revenues from different sources, including individual income tax, lottery, and sales tax by employing structural and time series models..