Jesus P.

Main role: I was responsible for creating a Data Lake that unified disparate data sources for comprehensive analysis. Applying ETL techniques to identify trends, patterns, and relationships in pharmaceutical product sales. I generated insights from the processed data to guide business decision-making, optimizing inventory and pricing strategies. I developed and automated Python scripts for data extraction, cleaning, and analysis, reducing report processing time by 40%.

Achievements: I led the transformation of the data department from reactive to proactive and predictive management. I applied machine learning models to identify consumption patterns and predict product demand, with a 15% increase in supply chain efficiency by implementing a predictive model that optimized stock levels, also reducing losses due to expiration. I analyzed IT support ticket data (incidents and requests) using Python and created interactive dashboards in Power BI to identify the main causes of problems and create efficient solution levels, reducing connectivity issues by 30% in branches and 70% in the main office.

I was the driving force behind sales data analysis, extracting valuable information from the Lanix ERP system. I used my expertise to perform exhaustive exploratory data analysis (EDA), uncovering correlations and business opportunities that were not visible at first glance. I generated an 8% increase in sales by identifying the highest-turnover products and their seasonal behavior, which allowed for precise adjustments to marketing strategies. I developed Business Intelligence dashboards in Power BI that offered a 360° view of the company's performance, empowering management to make quick and informed decisions. I automated 90% of data extraction and curation processes with shell scripts, freeing up team resources to focus on higher strategic value tasks.

My role was to analyze the root cause of incidents to implement definitive solutions. I used BI tools (Excel and Power BI) to analyze support tickets, transforming incident data into a map of operational improvements.

Achievements: 70% reduction in support ticket volume in the main office and 30% in branches by identifying and mitigating recurring connectivity issues. I led the migration of the database for the new ERP system, ensuring the integrity and operational continuity of the business without interruptions.