Data Scientist (Version Française)

Technical Skills: Python, Github, Jupyter, Excel, SQL, Power BI

Education

Master 2, Industrial Management IAE Bordeaux (2016)
Bachelor’s Degree, International Business Coventry University (2013)
DUT, Business and Administration Management IUT Saint Etienne (2012)

Projects

Customer Churn Prediction - Machine Learning

Development of a machine learning model to predict customer churn for a telecommunications company using Python. This project includes data analysis and fundamental applications of preprocessing and modeling techniques. It addresses class imbalance and performs feature engineering to enhance model accuracy. The result is a high recall (0.8-0.9), effectively identifying customers likely to churn. In conclusion, recommendations are made to improve model accuracy, strengthen customer retention, overall satisfaction, and long-term loyalty.

Uber Supply/Demand Gap - Data Analysis

Github Code

Developed a data analysis project to identify causes of Uber driver cancellations and car unavailability during trips to the airport. This project included time series analysis, data visualization, and advanced analytics. Key observations highlighted significant supply-demand gaps during morning and evening rush hours. This led to recommendations such as dynamic pricing, improved driver communication, and predictive analytics. These measures aim to improve service availability, customer satisfaction, and better understand underlying issues.

Professional Experience

Freelance Professional Coach (2019-2023)

Successfully organized and coordinated 50 professional events, including workshops and campaigns.
Administrative and strategic supervision ensuring operational and technical efficiency, achieving 70% profitability.
Developed and maintained client relationships, achieving a 90% satisfaction rate in 2023.

Production Manager, Veritable SAS (2017-2019)

Administrative and operational supervision of a project internalizing assembly and logistics in 2019, meeting 100% of qualitative and quantitative objectives.
Continuous improvement: Reduced stock shortages by 45%, processing time by 50%, processing errors by 35%, and non-conformities by 20%.