Summary
Kwame Edjah is a data engineer and deep learning researcher with eight years of experience building data-driven systems across finance, utilities, and public-sector programs. Currently consulting on Guidehouse’s New York State ERAP project, he blends production data engineering skills with academic rigor from ongoing PhD research in deep learning for signal processing and communications at the University of Cincinnati. His background spans Oracle and Hadoop ecosystems, PL/SQL and ETL work, and earlier hardware-focused roles in RF chipset verification and power systems engineering, giving him a rare full-stack perspective from silicon to cloud. He has taught and led workshops on Python, MATLAB, GitHub, and data visualization, demonstrating a talent for translating complex technical concepts to practitioners. Comfortable moving between legacy enterprise stacks and modern ML workflows, he’s especially adept at turning noisy signal data into actionable insights. Based in Cincinnati, he combines practical delivery on government-scale projects with active research that informs his engineering approaches.
8 years of coding experience
7 years of employment as a software developer
Master's degree, Electrical, Electronics and Communications Engineering, Master's degree, Electrical, Electronics and Communications Engineering at University of Cincinnati
Bachelor of Science (B.Sc.), Electrical and Electronics Engineering, Bachelor of Science (B.Sc.), Electrical and Electronics Engineering at Kwame Nkrumah' University of Science and Technology, Kumasi
English