Jean Dupont

Developed and deployed machine learning models including Random Forest, XGBoost, neural networks to optimize customer segmentation, increasing e-commerce platform revenue by 15%. Implemented automated data pipelines using Airflow and AWS, reducing data processing time by 40%. Collaborated with cross-functional teams to integrate predictive models in production applications using Docker and Kubernetes. Conducted internal workshops on best practices in MLOps and data visualization.

Built churn prediction models using Scikit-learn and TensorFlow, reducing churn rate by 10% for a telecom sector client. Analyzed massive datasets (> 10 TB) with Spark and SQL to identify key trends and provide strategic insights. Developed interactive dashboards with Tableau to present KPIs to non-technical stakeholders. Contributed to the migration of data processes to Azure, enhancing workflow scalability.

Conducted exploratory data analyses on client data to identify cross-selling opportunities, increasing sales by 8%. Developed logistic regression and clustering models (K-means) for marketing projects. Automated analysis reports with Python and SQL, reducing report generation time by 30%. Participated in writing technical specifications for data-driven projects.