Lasse Tyrväinen
About Lasse Tyrväinen
Lasse Tyrväinen is a Data Scientist and Data Engineer at Solita, where he has worked since 2017. He holds a Bachelor's and Master's degree in Computer Science from the University of Helsinki and has experience with various data tools and programming languages.
Work at Solita
Lasse Tyrväinen has been employed at Solita since 2017, where he holds dual roles as a Data Scientist and Data Engineer. His work is based in the Helsinki Area, Finland. Over the course of his seven years at Solita, he has contributed to various projects that leverage data science and engineering principles. His responsibilities include data exploration, analysis, and model building, utilizing a range of tools and technologies.
Education and Expertise
Lasse Tyrväinen completed his Bachelor's Degree in Computer Science at the University of Helsinki, studying from 2009 to 2015. He furthered his education by obtaining a Master's Degree in the same field from the University of Helsinki, which he completed in 2016. His academic background provides a solid foundation for his work in data science and engineering.
Background
Prior to his tenure at Solita, Lasse Tyrväinen worked as a Research Assistant at the Helsinki Institute for Information Technology from 2011 to 2015. He also gained experience as a Developer at Cloud'N'Sci Ltd for 11 months in 2015-2016. These roles contributed to his skill set and understanding of data-related challenges.
Technical Skills
Lasse Tyrväinen possesses a diverse technical skill set that includes proficiency in Python, AWS tools, and PostgreSQL/PostGIS. He occasionally utilizes R for its extensive library ecosystem. Currently, he is learning to use Tableau for data exploration, reflecting his commitment to continuous learning and adaptation in the field of data science.
Professional Development
Lasse Tyrväinen emphasizes the importance of understanding that achieving good results in data science extends beyond machine learning. He enjoys learning new tools for data exploration, analysis, and model building, which indicates his proactive approach to professional development in the rapidly evolving data landscape.