Eric Agyemang, Ph.D. Email & Phone Number

Canada

Normal, Il, Us

Duties Assigned.• Served as primary lab instructor to Python Programming for Data Science and Data Analysis - (IT 166),Script Languages and Automation - (IT 170), Structured Problem Solving Using the Computer (JavaProgramming) - (IT 168) classes, and Editor to coding video library of IT department of Illinois StateUniversity. Edited, Compressed, and processed over 500 videos/images and uploaded them on the school of IT coding streaming library for instructors and student access and use. These served as supplementary teaching and learning materials for coding classes in the department.• Grade students’ programming assignments and coding exams in a timely manner which require an in-depth knowledge of programming topics taught in class. Took students’ attendance, and monitored students participation in programming laboratory section of the class.• Met with professors for faculty meeting discussion, prepared instructional materials, held office hours, assist students to be good Python, Java, and C++ programmers, and proctor Python, Java, and C++ programming exams.• Created Java, C++, and Python scripts and algorithms (Predictive Analysis, ML, Deep learning, AI) forprediction and automation using real world data, implemented the algorithms, by applying them inmultidimensional space.• Performed data cleaning, data visualization, and data analysis using Java, Python, and C++; built predictive models, and model automation using Python; created automated integration dashboards that are result oriented using real word data for demonstration purposes and practice by students.

Normal, Il, Us

Duties Assigned.• Performed data query (Structured, Semi-Structured, and Unstructured data), data waggling, data quality automation, and created automated report generation dashboards that assist management in tactical and strategic decision making, saved up to 45 man hours per month.• Facilitated technical support and training on Moodle, Zoom, and Proctorio for faculty and students.• Presented technical solutions to non-technical audience, created 200+ process documents including video tutorials.• Facilitated university college workshops, organized weekly meetings, and presented weekly report to departmental heads.• Explored clustering techniques for Natural Language Processing (NLP) and analyzed text data.• Facilitated technical support and training on Summer Conferences to ensure the smooth flow of communication.• Explored ways to visualize and send daily report of test results to team members and faculty using Excel and VBA

Luxembourg, Lu

Duties Assigned.• Created data pipeline using AWS (EC2, S3, EMR, Redshift, Glue), Microsoft SQL server, and ETL tools (Oracle data integrator, and Informatica PowerCenter) for data cloud products (10 million observation of structured, semi-structured, and unstructured demographic, socio-economic, institutional variables data for Asian, African, and the emerging markets).• Created algorithms for insurance product sales and claim prediction which automate sales and claim planning. These resulted in saving up to 40 man hours per month. Created algorithms with Python using KNN in multidimensional space, achieved accuracy of 82%.• Implemented SDLC using agile and PLC to build technology capabilities, performed trend analysis using data for the period 2000 - 2019 on costs incurred on products in development. These unearth the relatively higher cost incurred on firm’s products in development, and informed management about the need to minimize such costs to appreciate profit.• Empirically compared RBF, Logistic Regression, Panel Regression, SVM, and Random Forest for predicting market performance which contributed to the development of product sales. These aid management in effective decision making and highlighted the need for increasing firm’s customer satisfaction for increasing premium.• Implemented Dynamic Pricing Tool, that adjusts product price based on market demand, increased revenue by 19%• Performed data visualization and generate automated report integration dashboard to monitor market trends. These aid management in strategic planning and tactical decision making on market development as well as selecting a profitable project to invest. Wrote report to management. These resulted in 45% increase in investment returns. [Power BI, Tableau]• Developed a service to automatically perform a set of unit tests daily on products in development. This helped to decrease the time used by the data science and analytics team to identify and fix bugs.

Duties Assigned• Used GCP to create data pipeline for data cloud products, expand and optimized data and data pipeline, ensured the consistency of optimal data delivery architecture throughout ongoing projects of the firm.• Optimized and redesigned firm’s data warehousing architecture to support the next generation product initiation. Built infrastructure required for optimal extraction of data from source system (Oracle database), integrated incremental data into a staging database (MySQL database), loaded into Data Mart which was the target system.• Managed the firm’s National database, performed data analysis with Power BI, Tableau, Python and R. Performed several queries using Oracle SQL, MySQL, Microsoft Server SQL, MongoDB, and Hadoop.• Collaborated with team members and used Git as a version control system to organize modifications and assign tasks, saved up to 40 man hours per month.• Ensured that data sets were kept separated and secured in the database across national boundaries. Performed execution of ETL test cases, and BI test cases and ensured that result set met with expectations of the Business Requirement Documents (BRD).• Ensured a higher degree of accuracy of firm’s data set, and a readily available and accessible data set from the database.• Performed trend analysis on fee recovered and bad debt data for the period of 2000 - 2015, used Python and SAP Bus for prediction of bad debt recovery and payments, achieved an increase in revenue by 18.5%.• Designed a survey using Cluster sampling approach, sampled Bono region of Ghana for survey on financing cash crop farming.• Prepared contingency plan for operational periods, built predictive models with Python, R, and Base SAS to predict and manage credit and other related risk which resulted in good quality loan portfolio.• Effectively worked with senior management to identify potential credit default risks and developed suitable mitigation strategies against such risk.

Lagos, Lagos, Ng

Duties Assigned• Managed Health Insurance and credit related data (Over 5 million observations of Complex Semi-Structured and Unstructured data), used Oracle SQL, MongoDB, and Hadoop to query big data used for analysis, used Tableau and Power BI for data visualization and reporting, created algorithm using Python for fee default and bad debt predictions which automates fees planning for operational periods.• Empirically compared predictive models (Logistic Regression and Ensemble models (Random Forest, AdaBoost, and Gradient boosting) using R, Base SAS, Python, and Apache Hive, performed model validation to confirm the new pricing tools’ ability to successfully replicate historical results. Performed variable selection using Variance threshold technique, achieved 25% increase in firm’s overall performance for the operational period.• Investigated imputation of missing data and the bias in-which such imputed data imposed on the prediction of lifetimes. Created automated claim payment schedule used for claim payments. This curbed the extant issues of customer complaints and dissatisfaction of delays in claim payments.• Developed an automated service used to perform daily unit tests on education and funeral policy. This decreased the time used by teams to identify and fix bugs. Saved the teams up to 35 man hours per month.• Used survival and clinical data (Over 25 million observations) to model and empirically evaluated low-rank approximation methods (QR, SVD, NMF) for obtaining PMI-based word embedding. The truncated SVD achieved the best performance on similarity and the analogy tasks.• Used Python and R to designed sampling scheme, chose Greater Accra, Bono, and Ahafo regions of Ghana using cluster sampling to estimate the average ARR, IRR, and ROI for Flexy-2 and Flexy-3 long term investment policies, achieved an increase in revenue by 25%.•Processed monthly data requests from by National Insurance Commission, Ghana, on clients premium payment.

Duties Assigned1. Field data collection2. Data analysis3. Report writing on the community profile.

Duties Assigned1. Field data collection2. Data analysis3. Proposal writing on the Community’s problems with It’s potentials.

Associate'S Degree, Data Science For Business

Master Of Science - Ms, It With Computer Science

Master Of Science - Ms, Applied Statistics

Bachelor Of Science - Bs, Actuarial Science