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Guillermo Garcia Otin has a diverse work experience in the field of data science and machine learning. In their most recent position at greenTEG, they are currently working as a Data Scientist. Prior to that, they worked at Finovesta as a Data Scientist and Machine Learning Engineer, where they focused on modeling time series strategies and implementing NLP techniques for automated investing. Before that, Guillermo was a Software and Deep Learning Engineer at Tu Dortmund University, where they focused on developing deep learning models for word spotting in historical document images. Guillermo also worked as a Machine Learning Engineer at Universidad de Zaragoza, where they worked on image retrieval and place recognition using deep neural networks. Additionally, they have experience as a Software Developer at Dédalo, where they worked on deriving insights from data and collaborating with the engineering team. Guillermo started their career as a Data Analyst at Proycon. Overall, they have extensive experience in Python, deep learning, machine learning algorithms, and data analysis.

Guillermo Garcia Otin completed their Bachelor's degree in Industrial Engineering from Universidad de Zaragoza from 2014 to 2018. Guillermo then pursued a Master's degree in Industrial Engineering from the same university, which they completed from 2018 to 2020. During their time as an undergraduate, they also spent a year studying Computer Science at Universitatea Transilvania din Brașov from 2016 to 2017.

In 2019, Guillermo furthered their education by enrolling in TU Dortmund University, where they pursued a Master's degree in Artificial Intelligence, specializing in the field of Artificial Intelligence. Guillermo completed this program in 2021.

Outside of their formal education, Guillermo obtained two additional certifications. In 2019, they obtained a B2 Certificate in English from Cambridge Assessment English. Guillermo also obtained a C1 Zertifikat from TU Dortmund University in the same year.

Based on the provided information, it is important to note that no assumptions outside of the given experiences can be made.