Marco F. Larrea Schiavon
About Marco F. Larrea Schiavon
Marco F. Larrea Schiavon is a Senior Data Scientist with expertise in artificial intelligence models for fraud prediction and credit scoring. He holds a PhD in Mathematics from the University of Leeds and has experience in data processing, visualization, and genomic data analysis.
Work at Umba
Marco F. Larrea Schiavon has been serving as a Senior Data Scientist at Umba since 2021. In this role, he focuses on the design and execution of artificial intelligence models, particularly in areas such as fraud prediction, credit scoring, and intelligent budget allocation. His work involves creating data processing pipelines and visualizing complex results to support decision-making processes within the organization.
Education and Expertise
Marco completed his Doctor of Philosophy (PhD) in Mathematics at the University of Leeds from 2015 to 2019. His doctoral research concentrated on Mathematical Logic, specifically categorical models for Homotopy Type Theory. Prior to this, he earned a Master's degree in Mathematics from Universidad Nacional Autónoma de México from 2012 to 2015, where he also collaborated on papers related to genomic data analysis during his internship. He holds a Bachelor of Science (BS) in Mathematics from the same university, completed from 2007 to 2011.
Background
Marco has a diverse background in mathematics and data science. He began his academic journey with a Bachelor of Science in Mathematics, followed by a Master's degree, and culminated in a PhD. His professional experience includes a role as a Data Scientist at Synx.co from 2019 to 2020 and as Co-Founder and CTO at LASI from 2020 to 2021. He has developed skills in data processing, database manipulation, and the use of computer proof assistants such as Coq and Agda.
Research Contributions
During his academic career, Marco was involved in significant research activities. His PhD studies included a focus on Mathematical Logic and categorical models for Homotopy Type Theory. Additionally, he interned at the Mexican National Genomics Institute (INMEGEN) during his Master's studies, where he analyzed genomic data using R and the Bioconductor library. This experience contributed to his expertise in genomic data analysis and reinforced his analytical skills.