Our Team
Mogital analytics people are highly skilled analytical experts with advanced degrees who utilize their skills in both technology and sciences to find trends and manage data. We’re committed to solving complex business challenges using the latest technology and data resources combined with our creative and collaborative strategic approach. Learn more about some of our talented professionals below.
Osei Tweneboah, Ph.D
C.E.O, Principal Data Scientist
​
​
Osei is an Assistant Professor of Data Science at Ramapo College of New Jersey, specializing in Machine Learning, Stochastic Analysis, and Scientific Computing with applications to Big Data Analytics and Complex data sets arising in Finance, Public Health care, Geophysics, etc.
​
Osei is an accomplished researcher with over 23 peer-reviewed articles in Data Science and Statistics, Computational Science, and Applied Mathematics. He teaches Applied Statistics, Data Analytics in Python, Data Analysis and Visualization, Machine Learning, and several other courses at the undergraduate and graduate levels at Ramapo College.
​
Osei attended the University of Texas at El Paso, where he received his Ph.D. in Computational Science, M.S. in Mathematics, and a Graduate Certificate in Big Data Analytics.
​
Linda Amoafo
Principal Data Scientist
​
​
​
Linda is a Doctoral student at the University of Utah within the Department of Population Health Sciences with an emphasis in Biostatistics. Her research focuses on developing methods for analyzing multicollinearity among multiple exposures and causal inference in multi-stage modeling. She has cross-disciplinary expertise in Statistics, Data Science, and Biostatistics.
​
Linda is currently a graduate research assistant at the CCTS Study Design and Biostatistics Center at the University of Utah School of Medicine. In her collaborative research, Linda has worked on observational and experimental studies using various statistical modeling techniques.
​
Linda received her M.S. in Statistics from Northern Arizona University.
​
Seth Gyamerah
Data Scientist
​
​
Seth is a Lecturer and a Doctoral student at C.K Tedam University of Technology and Applied Sciences (C.K. Tedam) in Navrongo, Upper East Ghana. His research focuses on developing novel classification hybrid techniques to analyze the polarity of the contextual dataset. Seth teaches Data analysis in Python, Business Intelligence and Data mining, Data visualization, Machine learning, and several other courses at the undergraduate level at C.K. Tedam. He has worked as a Data Analyst consultant for companies like Peg Africa Ghana, Ecom Agro trading Ghana, and others.
​
Seth received his Master of Science in Big Data Analytics and a Postgraduate Certificate in Machine Learning from Novosibirsk State University (NSU), Russia – Federation.
Ransmond Berchie
Data Scientist
​
​
​
Ransmond received his Master’s in Statistics from Northern Arizona University and is a Ph.D. Biostatistics student at the Population Health Science Department of the University of Utah. His research interest broadly spans causal inference, survival analysis, longitudinal data analysis, and pharmacoepidemiology. He is currently working on using EHR data of patients at-risk of sepsis to learn an optimal antibiotic initiation rule. He is an experienced scholar in the field of Statistics and Biostatistics.
Currently, he is a Research Assistant at the Study Design and Biostatistics Center at the University of Utah. In this role, he collaborates with various highly-trained professionals – physicians, pharmacists, MS- and PhD-trained statisticians – on innovative projects serving as the leading or secondary biostatistician/analyst. He is a member of the American Statistical Association and a recipient of the Lester R. Curtin Award.
Prince Sekyi
Data Scientist/Engineer
​
​
Prince is an Assistant Professor of Mathematics at Brookdale Community College, New Jersey, and Lead Data Science Instructor with TDX, where he teaches and prepares upcoming Data Scientists, Data Engineers, and Data Analysts for the job Market. He specializes in Data Cleaning, Data Wrangling, Developing and Maintaining Data pipelines, Machine Learning, Data Analysis, and Visualization using Python, R, PowerBI, and Tableau software.
​
Prince is a Tenured faculty, and he uses good communication and interpersonal skills to make abstract mathematical topics easy and understandable to his students; These skills are evident in his analytical reports and presentations. He is very concise and precise in his work.
​
Prince attended East Carolina University, where he graduated with a master’s in mathematics with Statistics Concentration and a master’s in quantitative economics and Econometrics.