Kostas Mouratidis
About Kostas Mouratidis
Kostas Mouratidis is a Senior Research Engineer specializing in Machine Learning at Thomson Reuters in Zug, Switzerland, where he has worked since 2023. He has a diverse background in software engineering and data science, with previous roles at Oracle and Zeta Global.
Work at Thomson Reuters
Kostas Mouratidis currently serves as a Senior Research Engineer in Machine Learning at Thomson Reuters, a position he has held since 2023. His work is based in Zug, Switzerland, and follows a hybrid work model. Prior to this role, he worked as a Senior Software Engineer in Machine Learning at the same company for three months in 2022. During his tenure, he contributed to the development of Westlaw and other Thomson Reuters products, showcasing his expertise in machine learning applications within legal technology.
Education and Expertise
Kostas Mouratidis holds a Master of Science in Data Science from the International Hellenic University, which he completed from 2018 to 2019. He also earned a Bachelor's degree in International & European Studies from the University of Macedonia, where he studied from 2010 to 2017. His educational background provides a solid foundation for his work in machine learning and data science, equipping him with the necessary analytical skills and knowledge to excel in his field.
Background
Before joining Thomson Reuters, Kostas Mouratidis gained extensive experience in software engineering and data science. He worked at Oracle as a Software Engineer and later as a Senior Software Engineer from 2020 to 2022 in Prague, Czech Republic. His earlier role at Zeta Global as a Data Scientist lasted for two months in 2019. Additionally, he began his career with an internship at Upgrade Consulting and Training in Thessaloniki, Greece, where he served as a Training Consultant and Academic Advisor in 2015.
Achievements
Kostas Mouratidis has engaged in various projects that highlight his skills in machine learning and software development. He experimented with using a small dense neural network to replace large language models, demonstrating his innovative approach to machine learning challenges. He has also worked on integrating Azure support into existing tools and participated in MLOps projects utilizing Python and AWS. His attempts to use Mixtral for rapid thesis generation reflect his commitment to exploring new technologies and methodologies.