Gražvydas šemetulskis
About Gražvydas šemetulskis
Gražvydas Šemetulskis is a data scientist with a PhD in Mathematics from Vilnius University. He has held positions at Adform, Three Thirds, and currently works at Vinted in Vilnius, Lithuania.
Current Role at Vinted
Gražvydas Šemetulskis is currently employed as a Data Scientist at Vinted, having joined the company in 2023. His role involves leveraging data analysis and machine learning techniques to enhance the platform's operations and user experience. Vinted is a leading online marketplace for second-hand clothing, and his contributions are aimed at optimizing data-driven decision-making within the organization.
Previous Experience in Data Science
Prior to his current position at Vinted, Gražvydas Šemetulskis held several roles in the field of data science. He worked at Adform from 2016 to 2019 as a Data Scientist, where he focused on data analytics and modeling. He then advanced to the role of Senior Data Scientist at Adform for a brief period in 2019 to 2020, before moving to Three Thirds as an AI Engineer from 2020 to 2023. His diverse experience in these roles has equipped him with a strong foundation in data science methodologies.
Education and Academic Background
Gražvydas Šemetulskis completed his academic studies at Vilnius University, where he focused on Mathematics. He earned his Bachelor's degree from 2007 to 2011, followed by a Master's degree from 2011 to 2013. He continued his education at the same institution and achieved a Doctor of Philosophy (PhD) in Mathematics from 2013 to 2018. His extensive academic background has provided him with a solid theoretical understanding of mathematical principles, which he applies in his professional work.
Professional Development in AI and Data Science
Throughout his career, Gražvydas Šemetulskis has developed a strong expertise in artificial intelligence and data science. His role as an AI Engineer at Three Thirds involved implementing AI solutions, while his positions at Adform required advanced data analysis and modeling skills. This progression reflects his commitment to professional growth and his ability to adapt to the evolving landscape of data science and technology.