Rôles occupés
Back-end
Business Intelligence
Cloud
Building data processing applications in Azure. Working with Revenue data, creating and predicting KPIs.
Preprocessed high-dimensional datasets, utilizing automatic outlier removal via clustering. Improve machine learning model by applying feature selection, feature engineering, and explainable AI methods.
Thesis: Internal membership inference attack on private federated models. Gained hands-on expertise in machine learning pipelines, including data analysis, preprocessing, model validation, and explainability. Focused on NLP, time series, computer vision, and deep learning.
Projects with companies to improve their business processes. Developed Java applications in Scrum-based teams using version control (Git). Thesis: Developed Selenium automation software for Johnson and Johnson.
Built applications in C, Java, PHP, and Python. Integrated SQL databases into scalable applications. Applied business intelligence tools (Qlik, Tableau) for data-driven decision-making.
