Mariana Marchesino

Designed and executed end-to-end data processing workflows (ETL), cleaning, transforming, and structuring large experimental datasets using Python to optimize preprocessing times by 30%. Developed automated scripts for advanced statistical analysis and visualization, and translated complex experimental requirements into structured analytical models and technical documentation.

Collaborated within a multidisciplinary team under Agile/Scrum methodology, contributing to the strategic and methodological design of applied data solutions for inventory and process optimization. Supervised data cleaning, structuring, and curation of complex datasets, and developed interactive Streamlit dashboards for real-time data ingestion and visualization.

Designed practical analytical frameworks based on risk analysis, statistical data interpretation, and industrial quality regulations. Guided students in analytical reasoning, systematic problem-solving, and adherence to technical documentation standards.

Managed data-driven quality control and physicochemical databases for the industrial sector, supervising information validation cycles and ensuring 100% data integrity. Applied rigorous regulatory and international standards, and prepared technical documentation, SOPs, and compliance reports.

PhD in Agricultural Sciences (Food Science) in final thesis stage.

Pursuing a Bachelor's Degree in Data Science (Complementary Cycle), expected to complete in December 2027.

Completed a Machine Learning Developer Program with practical projects.

Earned a Data Science Technician Degree.

Completed a Specialization in Food Technology.

Earned a Bachelor's Degree in Nutrition.