I, Eduards Skukis, was born in 1981 in Preili, Latvia. After successfully completing my Bachelor's degree in 2002, I pursued a Master's degree at the esteemed Riga Technical University (RTU), graduating in 2004. Following my academic journey, I commenced my career as a researcher at RTU's Institute of Materials and Structures.
Over the past two decades, I have accumulated extensive experience in mechanics, specializing in numerical simulations and practical experiments, particularly in vibrations and modal analysis. I've had the privilege to contribute to research projects supported by esteemed institutions such as the European Space Agency, the European Regional Development Fund, the European Social Fund, and the framework projects of the European Commission. These opportunities have allowed me to significantly advance knowledge in my field and engage in pioneering research endeavors.
In tandem with my mechanical pursuits, I have nurtured a deep interest in programming since my school days. As I progressed in my career, I seamlessly integrated my programming skills with my research activities, enhancing my analytical capabilities and broadening my horizons.
Three years ago, I began transitioning into Data Science, aiming to apply my knowledge in this field. I completed several courses on Stepic ("Python Generation", Introduction to Data Science and Machine Learning, Interactive SQL Trainer) and further expanded my expertise through the Skillbox Data Science PRO program. This education provided me with a solid foundation in data analysis, machine learning, and working with databases.
Most recently, I worked as a Data Analyst at Startap Solution | Noranet.io, where I focused on data processing and analysis. My responsibilities included optimizing Zoho CRM processes by developing API requests and implementing lookup fields to streamline data entry. Additionally, I worked with Thing Board, analyzing and generating telemetry data, creating interactive dashboards and widgets, and writing rules for effective telemetry processing. This role deepened my expertise in working with databases, querying large datasets, and handling JSON-formatted data.
With a strong foundation in research, engineering, and programming, I am eager to continue growing in Data Science and applying my analytical skills to solve complex problems.