Oussama E.

At Scale AI, I held a Senior Data Analyst role focused on data performance and quality within large-scale AI environments. I developed advanced analysis and quality control tools in Python, identifying complex anomalies in massive datasets and improving AI deliverable accuracy by over 30%. I automated analytical and reporting workflows using Python scripts, complemented by Java micro-services for ingestion and transformation, reducing processing times by 40%. I also analyzed the performance of various AI models, optimized data pipelines by combining SQL, Python, and Java, and collaborated closely with ML, product, and QA teams to stabilize guidelines and enhance the quality of highly complex projects.

Implemented automation for data extraction from WMS G-Stock and ERP SAP, improving overall workflow efficiency. Created scalable data pipelines to ensure smooth data flow between platforms, reducing manual intervention and improving transfer efficiency. Led the centralization of warehouse data on Power Apps, optimizing data collection and enabling better management for more effective decision-making. Improved system performance by optimizing queries and data flows. Tools and technologies: Power Apps, WMS G-Stock, SAP, Python, SQL, Power BI, Azure

Developed a business application in VBA/PostgreSQL automating archiving, traceability, and warranty management, with integrated alerts, document generation, and email sending. Automated the data flow through interactive forms and structured transfer to a PostgreSQL database, reducing processing time by 400%. Measurable business results: €16k/year savings on repair budget and 80% reduction in processing times.