Silvana Avramska Lukarska
About Silvana Avramska Lukarska
Silvana Avramska Lukarska is a Data Scientist with a strong academic background in mathematics and extensive experience in data analysis. She currently works at Blue River Technology and has previously held positions at Samsung NEXT and Karlsruhe Institute of Technology.
Work at Blue River Technology
Silvana Avramska Lukarska has been employed as a Data Scientist at Blue River Technology since 2021. In this role, she applies her expertise in data analysis and programming to contribute to the company's projects. Her work involves utilizing advanced data science techniques to enhance product offerings and improve operational efficiency.
Education and Expertise
Silvana studied Mathematics at the Karlsruhe Institute of Technology (KIT), where she earned a Master of Science (M.Sc.) from 2009 to 2011. She is also a PhD candidate at KIT. Additionally, she completed a Bachelor's degree in Applied Mathematics at the Technical University of Sofia from 2005 to 2009. Silvana further developed her skills by obtaining multiple Nanodegrees from Udacity in Data Science, Data Foundations, and Computer Vision.
Background in Data Science
Silvana has a comprehensive background in data science, having previously worked as a Data Analyst/Scientist at Samsung NEXT for nine months in 2019-2020. She also served as a Data Analyst at Nasekomo for ten months in 2018-2019. Her experience includes a significant tenure as a Research Associate at Karlsruhe Institute of Technology (KIT) from 2011 to 2019.
Technical Skills and Tools
Silvana possesses strong programming skills in R and Python, which she utilizes for data analysis and modeling. She has hands-on experience with SQL for data management and analysis tasks. Additionally, she is proficient in data visualization tools such as Tableau, allowing her to present data insights effectively.
Mathematical Foundation
Silvana has a strong foundation in applied mathematics, which enhances her analytical capabilities in data science. Her educational background in mathematics equips her with the necessary skills to tackle complex data challenges and derive meaningful insights from data.