Sarah Matoub
Engineer in Statistics and Epidemiological Modeling at Umr Astre @CIRAD
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WORK HISTORY
Engineer in Statistics and Epidemiological Modeling at Umr Astre @CIRAD
Montferrier-sur-Lez, FR
EDUCATION
University of Montpellier
Master 2 (M2), Biostatistics
University of Montpellier
Bachelor, Mathematics
University of Montpellier
Master 1 (M1), Statistics and Data Science
ABOUT SARAH MATOUB
Currently working as a Statistical Engineer at UMR ASTRE (CIRAD), I am actively seeking a permanent position as a Data Scientist, starting from October 2025. My goal is to join a dynamic team where I can leverage my data analysis skills while continuing to grow and learn in a stimulating environment. As part of the European SPIDVAC project, I worked within a multidisciplinary team to identify the socio-economic determinants influencing livestock vaccination. To achieve this, I analyzed complex datasets from field surveys conducted in Senegal and national data from seven West African countries. I cleaned, structured, and analyzed these datasets using advanced statistical techniques, including factorial analyses (such as Multiple Factor Analysis), principal component–based mixed-effects logistic models, and LASSO regularization. I also compared different calibration methods, combining frequentist and Bayesian approaches using R (packages such as lme4 and rstanarm for modeling, dplyr and tidyverse for data management). In parallel, I contributed to supervising a field survey, which deepened my understanding of the challenges of collecting primary data in rural contexts. I also provided technical support to other team members on coding and statistical modeling, helping to foster a collaborative working environment. My work is driven by strong analytical rigor, the ability to manage and structure complex datasets under tight deadlines, and a continuous willingness to learn and explore new methods. Let’s connect if you’re interested in discussing my background and how I can contribute to your company. I’d be happy to exchange with you!
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