adzqx8@r.postjobfree.com

linkedin.com/in/soduromintah

309-***-****

Data Analyst, Data Scientist or Business Analyst

Education

Master of Science (MS) Data Analytics. GPA 3.71

University of Maryland University College

Adelphi, MD.

August 2014 – December 2016

Bachelor of Science (BS), Mechanical Engineering

Kwame Nkrumah University of Science and Technology

Kumasi, Ghana.

September 1964 – June 1968

Summary of my Strengths

Data and Statistical Analytics Predictive Modeling Business Analytics Quantitative Skills Qualitative Skills SAS Python R SQL MS Office Suites Tableau Continuous Improvement Strategies Effective Communication Industrial Engineering MS Excel with Visual Basic, VLOOKUP, Pivot Tables Relational Databases Data Visualization

Two and half years’ experience as a Data Analyst Professional and Trainee. Built several predictive models using data analytics and visualization tools, including SAS, R, Python, and SQL to query databases, and retrieved data. MS suites and Tableau.

Over twenty years’ experience as an Industrial Engineer (IE) and progressed to Chief and, subsequently, Director, Industrial Engineering and Management Information Systems (MIS) in a Primary Aluminum Smelter. Developed continuous improvement, cost reduction and performance enhancement strategies including performance-based incentive programs for the smelter, using MS Excel with Visual Basic.

Consulted on manufacturing operations for a beverage bottling company.

Career Summary

Personal Time, Relocation to the US, Washington, IL

-Data Scientist and Analytics Trainee & Professional

-Went back to school to acquire MS Data Analytics degree.

Alfa Wireless Company, Tema, Ghana

-Facility Manager, Internet Service Provider (ISP)

Kasapreko Beverage Bottling Company, Accra, Ghana

-Consultant & Member of the Board

VALCO - Kaiser Aluminum Corporation, Tema, Ghana

-Director, Industrial Engineering (IE) & Management Information Systems (MIS).

2014 – 2016

2002 – 2007; 2010 – 2014

2007 – 2010

1990 - 2002

Professional Experience

Data Scientist & Data Analytics Trainee & Professional 2014 to present

Relocated to the US and studied to acquire a Master’s degree in Data Analytics.

Built Predictive Models in Decision Tree, Neural Network, Linear and Logistic Regression and Ensembles using SAS Enterprise Miner software, Python, R-programming, and MS Visual Basic and SQL to query databases and retrieved data. Used the Framingham Heart Study data set and Readmissions data set to make predictions related to the incidence of heart attack, or readmissions to hospital.

Developed an analytical model based on Botch Company’s manufacturing data captured on parts as they went through their manufacturing operations. The model predicted the parts that would fail quality control tests and allow pre-emptive removal of them from the process. The data set was heavily class imbalanced with the target class of interest, i.e., the failed parts, constituting only 0.57% of the total observations. The key task was to train the model to detect these rare events well. The insights gained led to the selection of the best analytics techniques to build a robust predictive model.

Performed Big Data Analytics and Text Mining using IBM Watson Analytics, IBM Bluemix Cloud Computing, Hadoop Ecosystem, and Spark Ecosystem.

Accomplished Data Visualization using Tableau Data Visualization software.

Acquired familiarity with the following modeling software: Predixion, BigML, and Rapid Miner.

Kasapreko Bottling Company, Accra, Ghana 2007 – 2010

Consultant & Member of the Board

Determined the relative effectiveness of two bottling lines and recommended replacement of the worse line with one like the best, albeit, more expensive line. The cost difference would be defrayed within two years, from reduced downtime, increased throughput and lowered operating cost. This was important to the company given the highly competitive environment of the beverage bottling business.

Developed for the company a policy procedure for initiating and approving capital expenditure projects, including execution and monitoring.

Appointed to the Board of Directors of the Company.

Valco – Kaiser Aluminum Corporation, Tema, Ghana 1990 - 2002

Director, Industrial Engineering (IE) & Management Information System (MIS)

Managed the IE Department of an aluminum smelter as Chief Industrial Engineer.

Designed new key strategies for plant performance improvements and measures.

Developed a system using MS Excel/Visual Basic to model the lake levels of the reservoir of the hydroelectric dam that supplied electric power to the aluminum smelter to forecast power availability, the most important input, to the smelter. This provided better power projections and led to better planning of the operations.

Developed a system, using MS Excel/Visual Basic, such that the aluminum metal produced daily by the fifty electrolytic cells in a line was siphoned by groups of three cells, and by the quality of the metal in the cells, while optimizing the travel distances between the fifty cells covered by the siphoning crew. This system generated a siphoning schedule that segregated the highest quality metal, avoiding adulteration by less pure metal, as well as optimizing the crew’s metal siphoning performance.

Aided senior management with value adding data analysis and recommendations to solve operating problems.

Developed a company-wide performance-based incentive program that covered about 1,500 employees. This program tracked the performance in the main key performance indicators (KPI’s) of the aluminum smelter and translated them into graduated personal earnings. This was a huge success for company and employees as employees could directly relate their incomes to their job performance.

Led the Plant to implement the then innovative data processing system that enabled data to be captured once at the source and eliminated centralized data entry operations.

Introduced a Stores and Purchasing computerized system that enabled an enhanced inventory control and management for the smelter. This eliminated long queues at the stores checkout counter experienced by technicians that needed to obtain materials for work at hand, among other benefits. An estimated 2,500 man-hours per month are saved as the technician can now make requisitions from his worksite and have them staged by the stores staff well before he shows up to pick the orders.

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