I am Noé Carème Fouotsa, a bilingual (French and English) data scientist based in Canada with over five years of experience in data analytics, statistical analysis, and data visualization. I specialize in database cleaning and the development and deployment of machine learning models to address challenges in regression, classification, time-series analysis, and clustering. I also automate data analysis processes to help organizations reduce repetitive tasks and enhance operational efficiency. My expertise includes creating and maintaining dynamic dashboards that deliver real-time insights for both operational and strategic decision-making.

I hold a Ph.D. in Operations Research from the University of Stellenbosch and leverage tools such as Python, SQL, Power BI, Tableau, R, and SAS to generate actionable data insights. I am committed to advancing epidemiology and public health through data science solutions that have a meaningful impact across industry, public health, and academia.

Institut national de santé publique du Québec, the Centre de recherche du CHUM, Canada Research Chair in Shared _Decision Making and Knowledge Translation (Université-Laval) and Institute of Pharmacology research Mario Negri (Italy). I hold, PhD degree in Epidemiology, Specialist degree in applied pharmaceutical research from IRCCS Istituto di Ricerche Farmacologiche Mario Negri and a Laurea in Biostatistica e Statistica Sperimentale from Università degli Studi di Milano-Bicocca. I am proficient in statistical software such as SAS, and R, and I specialize in data Hierarchical models, Linear models, Graphs (causal graphs), Logistic regression, Binomial regression, Poisson model, Survival analysis, Treatment of missing data, Oriented cyclic diagrams, Mixed linear models, Sample size calculation, Treatment of systematic bias, Clinical trial statistics, Mendelian analyses, Meta-analyses, Bootstrap, Recurrent event analyses, and statistical modeling. My passion lies in advancing public health through rigorous data analysis and research.