Lukas Norbutas
About Lukas Norbutas
Lukas Norbutas is the Team Lead of Data Science & Analytics at Vinted, where he has worked since 2021. He holds a PhD in Sociology from Utrecht University and has extensive experience in data science and analytics, having previously worked in various roles including Machine Learning Engineer and Data Janitor.
Current Role at Vinted
Lukas Norbutas serves as the Team Lead of Data Science & Analytics at Vinted, a position he has held since 2021. In this role, he oversees data science initiatives and analytics projects, contributing to the company's strategic decision-making processes. His experience in machine learning and data analysis supports Vinted's mission to enhance user experience and optimize operations.
Previous Experience in Data Science
Prior to his current position, Lukas worked at Vinted as a Machine Learning Engineer from 2019 to 2021. His responsibilities included developing machine learning models and algorithms to improve data-driven decision-making. Before joining Vinted, he gained experience as a Data Janitor at RAIT from 2012 to 2013 and as a Freelance Company Analyst at Euromonitor International from 2013 to 2014.
Educational Background
Lukas Norbutas has an extensive academic background in sociology and social research. He earned a Bachelor's degree in Sociology from Vilnius University from 2009 to 2013. He then pursued a Master of Science in Sociology and Social Research at Utrecht University from 2013 to 2015, followed by a PhD in Sociology at the same institution from 2015 to 2020. Additionally, he participated in a research visit at Stanford University in 2018 for 11 months and completed an exchange program at Lund University in 2012.
Research and Academic Contributions
During his academic career, Lukas Norbutas worked as a Research Assistant at Utrecht University from 2013 to 2015. In this role, he contributed to various research projects, applying his knowledge of sociology to real-world issues. His research experience complements his professional work in data science, allowing him to apply analytical skills to both academic and industry settings.