Nassiratou YANKENE

In the Directorate of Multilateral Surveillance and Macroeconomic Stability, I work on: -Contributing to regional macroeconomic surveillance, statistical harmonization, and data-driven policy analysis. -Collecting, validating, and analyzing regional economic indicators, as well as developing analytical reports and methodological documentation to support economic convergence and regional integration. -Operating at the intersection of statistics, data science, and economic policy within a multilateral institutional environment.

In the DataLab of Rennes University, I work on: -Developed predictive algorithms for chronic and renal disease progression. -Worked with SNDS (French National Health Data System) and PMSI databases in a regulated environment. Conducted data processing, cleaning, and validation to ensure high-quality analyses. -Performed rigorous model testing, including Renalgo, to detect chronic disease patterns. -Produced analytical reports and dashboards to support clinical and policy decision-making. -Maintained methodological documentation and traceability of all analyses.

As a Data Scientist, I contributed to the development of movie recommendation systems. Specifically: -Developed ETL pipelines, including web scraping and JSON data processing. -Built movie recommendation systems using TensorFlow and Python. -Designed and implemented classification models to enhance personalized recommendations. -Analyzed user data to optimize recommendation algorithms. -Collaborated with development teams to integrate models into production pipeline

Bolloré – Logistics Delay Prediction Extracted and processed data from Bolloré cloud systems. Developed classification and regression models to predict ship delays. Built an interactive Streamlit dashboard to visualize predictions. La Banque Postale – KYC Remediation Project Analyzed client data for KYC compliance and fraud detection. Wrote complex SQL queries and developed risk models. Optimized workflows using SAS, SQL, and Dataiku.

Worked on a project focused on interpretable modeling of disease progression, including: Analysis and development of machine learning algorithms for predicting disease evolution. Implemented neural network architectures with attention mechanisms. Applied Natural Language Processing (NLP) techniques to clinical data. Explored model interpretability to provide actionable insights for healthcare decisions.

Dans le cadre de fin de formation d'Ingénieur des Travaux Statistiques (ITS ) a l’ENSEA d’Abidjan,j'ai effectué un stage à l'ARTCI, au sein de la Direction de l'Economie des Marchés et de la Prospective (DEMP). J'ai travaillé essentiellement sur la thématique suivante : "L’Analyse des facteurs explicatifs de l’accès,l’utilisation et la satisfaction du service de l’Internet Mobile en Côte d’Ivoire ‘’