Carlos Diaz leads Metanalysis’s technology strategy as CTO, combining his strong academic background with a practical understanding of advanced analytics and artificial intelligence. A Ph.D. candidate in Interdisciplinary Studies at the University of Saskatchewan (Canada), Carlos specializes in predictive model development, statistical analysis, and applied machine learning.

He holds certifications as a KNIME Data Scientist – Machine Learning and KNIME Certified Trainer, and has completed specialized training in Weka, which supports his mastery of leading data science platforms. He has written articles on Medium and worked on projects including data collection from Canadian meteorological APIs, the development of neural network models to predict solar irradiance, data segmentation and clustering in social research, and the generation of synthetic data for data augmentation tasks.

Carlos designs and optimizes analytical workflows with tools such as n8n, KNIME, Python, and R, leading feature engineering, data visualization, automation, and model evaluation processes. Its rigorous approach and commitment to technological efficiency allow Metanalysis to offer scalable, robust solutions aligned with business needs.