Welcome to my website! I am Daniel Precioso, a highly experienced and passionate Ph.D. data scientist. My current research revolves around utilizing data science to achieve sustainable development goals and promote ecological transitions. With a degree in Physics, I bring a unique perspective to my work that enables me to develop innovative solutions to complex problems.
Throughout my over 4 years of career on industry, I have gained extensive experience in analyzing and interpreting data, implementing machine learning algorithms, and creating models that help organizations optimize their operations and make informed decisions.
As a data scientist, I am passionate about using my skills and expertise to make a positive impact on society. I believe that data science has the potential to transform the world for the better, and I am dedicated to exploring new ways to leverage this technology for the greater good.
PhD in Data Science, “Applications of Machine Learning and Data Science to the Blue Economy: Sustainable Fishing and Weather Routing” done under the supervision of David Gómez-Ullate. University of Cádiz, Spain.
MSc in Data Science. Universidad Politécnica de Madrid, Spain.
Bachelor’s Degree in Physics. University Complutense of Madrid, Spain.
Canonical Green is the start-up I’m part of, along with my co-founders David Gómez-Ullate and Javier Jiménez.
Green Navigation is the eco-friendly Google Maps of the sea! We are developing this tool in Canonical Green to help with the decarbonization of the shipping industry.
GOAL (Graphical Methods, Optimization, and Learning) is the research group at UCA I am currently member of.
UCA Datalab is a small all-in-one team from UCA - described as “the swiss knife of data science projects” - which I am very proud to be part of. I am also the admin their website!