I am a data scientist and chemical engineer with dual master's degrees in Bioengineering and Artificial Intelligence, specializing in advanced data analysis, machine learning, and data-driven digital transformation. My experience spans the pharmaceutical sector, life sciences, and regulated environments, where I work with large volumes of data from critical systems, industrial processes, and digital platforms, ensuring data integrity, traceability, and regulatory compliance.
My focus areas include statistical modeling and machine learning, predictive analysis and process optimization, automation of reports and dashboards, data integrity and governance, and digital transformation based on analytics and AI. I have demonstrated the ability to convert complex technical data into strategic business insights, improve operational efficiency, and develop analytical solutions applied to quality, engineering, production, and computerized systems.
I am passionate about roles such as Data Scientist, Senior Data Analyst, Machine Learning Engineer, AI Specialist, Business/Data Intelligence Analyst, Clinical Data Scientist, Data & Analytics Consultant, AI & Digital Transformation Specialist, and Data Scientist in Pharma, Healthcare, and Life Sciences sectors.
In my recent role as Senior Project Engineer at Cercal Group, I analyzed and structured large volumes of technical and quality data from critical systems like HVAC, utilities, cleanrooms, and pharmaceutical processes. I developed statistical analyses and trend evaluations to optimize processes and ensure regulatory compliance, implemented data analytics methodologies for KPI monitoring, deviations, and operational performance, and designed dashboards and analytical reports to support strategic decision-making.
Previously, as a CSV Engineer, I analyzed data quality, integrity, and traceability in LIMS, SAP, WMS, and production systems, implementing risk analyses and functional system evaluations, validating databases and automated systems, and strengthening data governance in regulated environments. Additionally, as a Clinical Data Scientist researcher at Pontificia Universidad Javeriana, I collected and cleaned data from chemoinformatics databases, developed machine learning models using Python, R, SQL, and C++, and collaborated with engineers and data scientists to create effective drug analysis solutions.
