Yannis Merzoug

● Data Processing and NLP: Collection and consolidation of national ambulance service data using natural language processing models, ensuring precise and comprehensive insights into regional needs. ● Statistical Analysis: Conducted advanced statistical analyses to identify risk areas and predict ambulance needs to ensure optimal coverage. ● Shiny Application Development: Designed and implemented an R Shiny application with a dynamic dashboard: ○ Activity Monitoring: Real-time visibility of ambulance operations, service specifications, and detection of shortages nationwide. ○ Simulation Model (Machine Learning): Allows regional health agencies to test various organizational scenarios and anticipate potential gaps, thereby optimizing ambulance distribution. ○ Financial Insights: Dedicated visualization of healthcare expenditures, illustrating the impact of organizational changes to facilitate better budget management.

https://cadyco.education ● Application Development: Content development and creation of a web platform (GitLab & R Shiny). ● Statistical Analysis: Creation of statistical indicators and geographical representations (Qgis & R), Data Management and Analysis (PostgreSQL, MySQL & R).

● Data extraction and processing (R, Excel, SAP). ● Data Analysis (R): Designed a statistical model to predict the lifespan of mechanical components. ● Creation of dashboards via an R Shiny application using an inventory optimization and forecasting model.

● Statistical studies on the influence of socio-economic variables on household mobility in Île-de-France via an econometric model. ● Study of variable selection bias, creation of a "hurdle" model describing the decision and intensity of mobility. ● Results: Report detailing descriptive and inferential analyses, as well as the interpretation of results.