Moussa ABDOULAYE

At Saft, a subsidiary of TotalEnergies specializing in high-performance battery design, I contribute to the digital transformation of the Aerospace, Defense & Performance (ADP) division by integrating SCADA systems, data pipelines, and AI solutions within a demanding industrial environment. → Developed SCADA applications using Ignition (Perspective & Vision) for real-time tracking and input of production quantities on manufacturing lines. → Designed data architectures: tag structures, historian systems, Python scripting, and SQL Server databases. → Implemented CI/CD pipelines for automated Ignition project deployment and gateway backups. → Integrated SCADA data with Power BI for live industrial reporting and interactive dashboards. → Automated data collection from production lines to standardize and streamline flows across departments. → Built and maintained Power BI dashboards to centralize key performance indicators (KPIs) and support decision-making. → Developed PowerApps solutions to enhance stock traceability, logistics efficiency, and production monitoring.

Combining Lean management with advanced data analysis techniques to drive continuous improvement and digitalization. In this role, my main responsibilities are: → Data Analysis : Collecting, processing, and analyzing data from sales and logistics to identify areas for improvement using statistical methods and machine learning algorithms to extract insights that optimize performance. → Digital Transformation : Developing and implementing Proofs of Concept (POCs) for dashboards and predictive tools based on Big Data, facilitating informed decision-making. → Deployment of the Data Analytics Strategy: Contributing to the Data Analytics strategy for McCormick's "Distribution France" division, in line with digitalization and efficiency objectives. → Distribution Roadmap : Analyzing strategic priorities, developing multi-factor business cases, and presenting recommendations to the Executive Committee (CoDir) to guide key decisions.

→ Improvement of an incident detection system in the continuous casting process by developing a Machine Learning model for detection. This includes clustering and classifying time series from real-time thermal data. → My responsibilities include data collection and preparation, model development, and practical implementation in a real industrial environment.