Health Care Machine Learning

Mark Leventhal

**************@*****.*** 917-***-****

I’ve been using data to drive business needs my entire career. An accomplished statistical, data, and text analyst with years of SAS® experience, I’m looking to intersect my passion for analytics with my passion for helping people. I love using data to tell a story and I use statistical analysis, data mining, text analytics, scorecard development, segmentation, market basket analysis and machine learning to weave my narrative. Through my vast expertise and ability to break down complex problems, I’ve also been recruited to teach several classes in data mining, text mining and SAS.

Industry Expertise

Health Care ● Educational Research ● Financial Services ● Credit Scoring ● Insurance ● Utilities ● Automotive ● Construction Equipment Reliability ● Aircraft Reliability ● Infrastructure ● Transportation ● Direct Mail ● Retail ● Packaged Goods

WORK EXPERIENCE

SAS Institute, Inc October 1995 - February 2023

Principal Analytical Consultant

In my long tenure at SAS Institute, I moved up the ladder, starting as an Associate Applications Developer and eventually being promoted through to a Principal Analytical Consultant. Along the way I successfully implemented internal and external customer projects ranging from a few weeks to year-long engagements. With my expertise in analytics and SAS programming, I served and impacted clients ranging from major US Banks and Fortune 100 and 500 companies to renowned colleges and universities. My category expertise is varied including finance, education, health care and utilities, to name a few. Using standard and newly developed analyses, I became known for meeting or exceeding customer requirements on all assigned projects, even being partially responsible for the creation of an educational analytics department based on my work developing predictive and descriptive analytics and modeling.

Projects Worked On

Health Care Claims Fraud (multiple projects)

Objectives:

Created predictive and descriptive models which flagged characteristics of fraudulent health care claims.

Developed population segments, using various clustering techniques, where fraudulent claims are more prevalent than the overall patient population.

Obtain scorecards which flag possible fraudulent claims when they are entered into company systems.

Advised clients on effective placement of fraud indicators on data entry screens.

Results:

Reduced fraud rates at several health insurance companies 15-25%.

Provided documentation and training in maintenance and occasional modification of models.

Customer Satisfaction Analysis

Objectives:

Assessed Customer Satisfaction analysis in health care and retail technology environments.

Performed data mining and text mining on customer service data and customer surveys to categorize customer service calls.

Determined characteristics of completed service cases.

Found characteristics of good performing customer service agents.

Results:

Increased customer satisfaction with call center employees.

Improved training for call center personnel.

Shortened time to resolution of customer issues.

Credit Scoring System Development/Data Mart Development (multiple projects)

Objectives:

●Modernize and centralize applications and financial institution systems to streamline and simplify.

●Create analytical data mart.

●Developed credit scoring models for applications, credit line assignment, fraud and renewal.

Results:

●Centralized data mart available to multiple departments.

●New analytical techniques increased model accuracy.

Cost Variance Modeling for Train Equipment

Objectives:

●Describe cost variations in repair locations for a train consortium.

●Reduce repair durations.

●Create an early warning system, designed to reduce unexpected equipment breakdowns.

●Improved ability to position locomotives in the network, reducing wait times for equipment availability.

Results:

●Uncovered $20 million per year in cost savings

Decreased repair process timeline.

Created a plan to optimize locomotive positioning in the transportation network.

Additional Experience

Aided software development for SAS Enterprise Miner – method creation and quality assurance.

Authored and taught a course in text analytics.

Taught classes in predictive and descriptive modeling, including neural networks, decision trees and regression models, and credit scoring

Created and led seminars and workshops at professional conferences.

Mentored customers and co-workers.

Wrote and edited SAS System documentation.

Created a large portion of NYC School Profiles.

CERTIFICATIONS

SAS Data Mining Using Enterprise Miner

SAS Visual Text Analytics in SAS Viya

SAS Expected Credit Loss Solution

EDUCATION

Master of Arts, Applied Statistics, State University of New York, Albany, NY

Bachelor of Science, Mathematics/Statistics, State University of New York, Albany, NY

Programming Experience – SAS, SAS Enterprise Miner, SAS Text Analytics, SQL, Python, SPSS, Fortran, Pascal, Basic, Microsoft Suite of Tools

PUBLICATIONS

Mark Leventhal, Lindsay Y. Datlow, Jay King, Mark Leventhal and Taylor C. Wallace, Association of Pork Intake with Cognitive Performance in Older Adults Enrolled in the National Health and Nutrition Examination Survey (NHANES), 2011–2014 Data Cycles, Journal of Alzheimer’s Disease 96 (2023).

Contact this candidate