Bridging 15 years of operational leadership with advanced data-driven engineering. I specialize in transforming complex business challenges into actionable insights through Machine Learning and predictive analytics.
Throughout my career at Droguería Rocar SRL, I evolved from managing large-scale procurement to architecting data solutions for the pharmaceutical supply chain. My recent formalization in Data Science & AI (ISTEA) serves to certify a trajectory built on real-world analytical implementations:
- Predictive Inventory Management: Built custom forecasting models to mitigate stock volatility and optimize procurement cycles in a high-stakes pharmaceutical environment.
- Business Intelligence & Dashboards: Designed and deployed automated reporting systems using Python and Power BI to monitor market trends and supplier performance.
- Process Optimization: Applied Machine Learning basics to streamline logistical workflows, significantly improving operational efficiency.
High-frequency data ingestion and real-time visualization system.
- Stack:
- Developed a pipeline to consume and clean real-time telemetry from the OpenF1 API. I focused on processing sensor data using Pandas for predictive performance analysis and exploratory data research.
Strategic research on international trade agreements and their impact on local pharmaceutical distribution.
- Stack:
- Leveraging 15 years of industry expertise to analyze trade data between Argentina and the US. I used SQL for data extraction and Power BI to identify supply chain optimizations and market trends.
Architecting scalable data labeling and automated workflows for AI training.
- Stack:
- Designing automated pipelines and applying Machine Learning basics to streamline the development of production-ready models. I focused on data labeling workflows and LLM integration to improve operational efficiency.
