Laurynas Jasiukėnas
About Laurynas Jasiukėnas
Laurynas Jasiukėnas is a Data Scientist at Vinted, where he has worked since 2020. He holds a Master of Science in Econometrics and a Bachelor of Science in Financial and Actuarial Mathematics from Vilnius University.
Work at Vinted
Laurynas Jasiukėnas has been employed at Vinted, also known as Kleiderkreisel, as a Data Scientist since 2020. His role involves contributing to backend Guild efforts, focusing on enhancing the data infrastructure and analytics capabilities of the platform. He has played a significant part in the initiative to replace Resque with Sidekiq, which aims to improve job processing efficiency within the organization. His work supports Vinted's mission to facilitate the buying and selling of second-hand items.
Education and Expertise
Laurynas Jasiukėnas holds a Master of Science (MS) in Econometrics and a Bachelor of Science (BS) in Financial and Actuarial Mathematics, both obtained from Vilniaus universitetas (Vilnius University). His educational background equips him with a strong foundation in quantitative analysis and financial modeling, which are essential skills in his current role as a Data Scientist. His expertise is further complemented by his experience in various financial and data-related positions.
Background
Laurynas Jasiukėnas began his career as a Claims Analyst at Lietuvos draudimas, AB in 2014. He transitioned to various roles, including Data Analyst at Ermitažas and Team Lead at Alma Littera Group. From 2017 to 2018, he served as a Financial Controller at Headex Group. He then worked as a Business Finance Controller for the Nordics at Avon from 2018 to 2019. Prior to joining Vinted, he worked as a Data Scientist at Brolis Sensor Technology from 2019 to 2020.
Achievements
Laurynas Jasiukėnas has made notable contributions in his field, including the development of the sidekiq-pool gem, which enhances the functionality of the Sidekiq job processing tool. His involvement in the initiative to replace Resque with Sidekiq at Vinted demonstrates his commitment to improving operational efficiency and performance within the company. These contributions reflect his technical skills and understanding of data processing frameworks.