Inventory Control Computer Science

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ADDRESS:

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Barry E. King, DBA

*** *** ******, ** *, St. Louis, MO 63104

Phone: 317-***-****

Email: *****.*.****@*****.***

EDUCATION:

• Post-Doctorate class in predictive analytics, Washington University in St. Louis, 2016

• Doctor of Business Administration, Indiana University, 1974-1979 o Dissertation: Master Production Scheduling in the Assemble-to-Order Environment: A Comparison of Two Techniques

o Majored in operations management, minored in computer science

• Master of Science work, Washington University in St. Louis, 1968-1971, in applied mathematics and computer science. Program interrupted by active military service. No degree earned. Thesis work on global convex linear decomposition algorithms

• Bachelor of Arts, University of Missouri -- St. Louis, 1965-1968. Mathematics major SUMMARY:

Director of analytics, senior analytics consultant, data analytics professor, department chair, quantitative modeler, and author with over thirty years’ experience. SKILLS:

• SAS

• SAS Enterprise Miner

• SAS OPTMODEL

• R

• Intermediate Python

• Descriptive statistics

• Predictive analytics

• Prescriptive analytics (operations

research)

• Gurobi

AREAS OF INTEREST:

• Predictive analytic

• Regression

• Classification

• Demand modeling

• Regression

• Time series

• Longitudinal analysis

• Inventory control

• Fixed quantity modeling

• Variable quantity modeling

• Network modeling

• Arc and node networks

• SAS network solver software

• Scheduling

• Quantitative modeling

• AMPL modeling language and Gurobi solver

• Pricing

• Fixed pricing development and then using the elasticity of demand

• Dynamic pricing

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PROFESSIONAL EXPERIENCE:

Director of Analytics, Qualex Consulting Services 10/2023 – present

• Lead a large scale predictive analytics project for Florida-based client

• Principal investigator for National Institutes of Health study on predicting length of surgeries and then scheduling them using operation research techniques. Proposal pending Senior Consultant, Qualex Consulting Services 2/2010-10/2023

• Lead a large scale SAS NETWORK programming problem for West Coast food producer

• Sole consultant on developing inventory control software in SAS for an electronics sales company

• Trainer for SAS Enterprise Miner for national casino

• Trainer for SAS JMP for a financial services company Associate Professor, Butler University 8/1991 – 5/2023

• Department chair for three years with twelve people reporting to me

• Principle investigator on numerous research studies with faculty and student research assistants

• Taught classes in database design (SQL), predictive analytics, and operations research Associate Professor, Marquette University 8/1985 – 7/1991

• Researched topics in operation management

• Taught classes in statistics, operations management, information technology, and MBA operations management

Assistant Professor, Ohio State University 8/1979 – 7/1985

• Taught MBA and Executive MBA operations management classes

• Participated in large-scale plant simulation to study the effects of Japanese plant policies on U.S. factories. The study appeared in Harvard Business Review and won the best paper award for Management Science

RELEVANT PUBLISHED RESEARCH:

• King, B.E., (2020), Assigning associates to shifts for an on-site before and after childcare program, International Journal of Recent Engineering Research and Development, 5(6), June 2020, 25-28.

• King, B.E., Davidson, J., (2019). Using Machine Learning to Predict Sales Conditional on Bid Acceptance. SSRG International Journal of Economics and Management Studies 6(11), 1-3.

• King, B.E., Pollard, T., Rice, J., & Siegler, J., (2019), Assigning Triaged Patients to Treatment Rooms in a Hospital Emergency Department, International Journal of Clinical & Medical Informatics, vol 2, issue 2, 71-81.

• King, B. E. & Rice, J., (2019), Analysis of churn in mobile telecommunications: predicting the timing of customer churn, AIMS International Journal of Management, 13(1), January 2019, pp. 1-15.

• King, B. E., Rice, J. L., & Vaughan, J., (2018). Using machine learning to predict average attendance at National Hockey League game, The Journal of Prediction Markets, 2018 Vol 12 No 2 pp 85-98.

• King, B. E. & Rice, J., (2018), Predicting attendance at Major League Soccer matches: a comparison of two techniques, Journal of Computer Science and Information Technology, December 2018, Vol. 6, No. 2, pp. 15-22.

• King, B. E. (2017). Predicting National Basketball Association game attendance using random forests, Journal of Computer Science and Information Technology, 5(1) pp. 1-14.

• King, B. E., Leach, A., Platt, M., & White, D. L., (2017). Scheduling surgical operations and the post- anesthesia care unit using work tours and binary programming. AIMS International Journal of Management, 11(1), 101-109.

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