Artur Siedlecki
About Artur Siedlecki
Artur Siedlecki is a Data Scientist in the User Success Team at SparkBeyond, where he specializes in SQL and employs programming languages such as Python and Pyspark for data analysis. He has a background in data analysis and business intelligence, with previous roles at Grupa Eurocash, PayU, and Allegro.
Work at SparkBeyond
Artur Siedlecki has been working at SparkBeyond as a Data Scientist in the User Success Team since 2021. In this role, he focuses on data analysis and employs various programming languages, including Python and Pyspark, to perform daily tasks. His expertise in SQL aids in database management and data manipulation, contributing to the team's objectives in enhancing user success.
Previous Experience in Data Analysis
Before joining SparkBeyond, Artur Siedlecki gained extensive experience in data analysis roles. He worked at Allegro as a Data Analyst from 2017 to 2021, where he developed his analytical skills over four years. Prior to that, he served as a Junior Business Intelligence Specialist at PayU for one year in 2016. His career began at Grupa Eurocash, where he worked as an Analyst from 2014 to 2016.
Education and Expertise
Artur Siedlecki holds a Master's degree in Informatics and Econometrics from Uniwersytet Ekonomiczny w Poznaniu, which he completed from 2014 to 2016. He also earned a Bachelor's degree in Economics with a focus on Business Strategies from the same university, studying from 2008 to 2011. His educational background provides a strong foundation for his work in data science and analysis.
Technical Skills in Data Science
In his current role and previous positions, Artur Siedlecki specializes in several technical skills essential for data science. He utilizes SQL for effective database management and data manipulation. Additionally, he employs advanced data visualization tools like Tableau for reporting purposes, particularly in the area of Search. His proficiency in programming languages such as Python and Pyspark enhances his capabilities in data analysis.