Djass Mbangdadji, M.S, MBA

Djass Mbangdadji, M.S, MBA

Senior Statistician

Djass Mbangdadji is Chief Statistician at EurekaFacts. His responsibilities include providing strategic orientation on the appropriate statistical and econometric techniques to address the project objectives and overseeing all statistical activities at EurekaFacts, including study design, data capture, analysis, interpretation and presentation. He directs an advanced analytics team of analysts conducting statistical, geospacial and thematic analysis using human-led analysis and machine learning data science projects

For more than 12 years, Djass has applied theoretical frameworks to practical business needs and leveraged analytical tools to bring about actionable solutions, using mathematical and inferential statistics. His expertise in data management and with statistical software such as Stata, SAS, SPSS, R, or SQL language allows him to write customized programs to apply the most recent developments in data mining. He has also led efforts to deliver data analytics using dashboards in Power BI, Tableau, Salesforce as well as geo-spatial visualizations in Arc GIS.

Djass’ areas of expertise include sample and sampling frame design, sample size calculation, multi-mode data collection, survey research analysis, statistical and predictive models including regression analyses (linear and non-linear regression, multivariate regression, logistic regression, multinomial logistic, ordinal logistic), analysis of variance or covariance, data mining (including supervised and non-supervised learning such classification, clustering, latent class analysis, neural network, decision trees, association rules), time series analysis, geographic information system, etc. He successfully applied those techniques to customer satisfaction studies, market segmentation, customer profile development, cost-effectiveness analysis, price sensitivity analysis, discrete choice modelling, descriptive or explanatory models, business forecast, chronological data, intervention analysis, location selection analysis, etc. for private firms, non-profit organizations, local governments and Federal agencies.

Djass holds an MBA degree with specialization in business analytics from the University of Maryland – Robert H. Smith School of Business, a Post-Graduate degree in Statistics and Econometrics and a MS in Mathematical Engineering from the University Toulouse III Paul Sabatier in Toulouse, France.