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.
• 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.
• 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.

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.
• 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.

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.
• 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.
• 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.
• 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.
• Implemented Dynamic Pricing Tool, that adjusts product price based on market demand, increased revenue by 19%

• 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).
• 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.

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.
• 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.
• 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.
• 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.

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