Cayetano Romero is a Data Scientist with nine years’ experience applying Big Data, process mining and predictive modeling across telecom, finance and public sector clients from Madrid. At Minsait he builds production-grade predictive systems, billing solutions on Cloudera stacks and Celonis-driven process mining deployments for companies like Telefónica, Mapfre and Inditex. His background in computer engineering and prior research on smart cities and mobility informs pragmatic ML solutions—such as cab-demand prediction and time-series association-rule analysis—grounded in real-world IoT data. He combines hands-on software development with analytics and dashboarding, delivering both models and the operational reporting that makes them actionable. Notably, he has contributed matching-name and tax-related analytics for public agencies and led international projects including work for Globe in the Philippines. Fluent in bridging research insights and enterprise-scale Big Data engineering, he thrives on turning complex processes into measurable business impact.
9 years of coding experience
Computer Engineering Degree (Information Systems), Computer Engineering Degree (Information Systems) at Universidad Pablo de Olavide
Contributions:11 releases, 124 pushes, 10 branches in 1 year
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