Anna Yakubava
About Anna Yakubava
Anna Yakubava is a Senior Business Data Scientist at Kinaxis, where she has worked since 2021. With extensive experience in data analysis and project management, she has a strong background in handling large datasets and expertise in the retail and e-commerce sectors.
Work at Kinaxis
Anna Yakubava has been employed at Kinaxis since 2021, currently holding the position of Senior Business Data Scientist. In this role, she applies her analytical skills to address complex data science challenges. Prior to her current position, she worked as an Advisory Analytics Developer at Kinaxis from 2020 to 2021. Her experience at Kinaxis highlights her capability in managing and executing projects within the data science domain.
Previous Experience in Data Analysis
Before joining Kinaxis, Anna Yakubava worked at Rubikloud Technologies as a Senior Data Analyst from 2018 to 2020. Her earlier experience includes a significant tenure at Infernotions Technologies Ltd, where she served as a Data Analyst from 2009 to 2013 and later as a Senior Data Analyst from 2013 to 2020. Additionally, she began her career as a Software Engineer at NIIEVMservice from 2007 to 2009. This diverse background has equipped her with a strong foundation in data analysis and software engineering.
Education and Expertise
Anna Yakubava earned her bachelor's degree in Software Engineering from Belarusian National Technical University, where she studied from 2000 to 2005. Her educational background supports her advanced skills in SQL, Python, Spark, and NoSQL databases. These technical proficiencies are essential for managing large datasets and conducting exploratory data analysis, particularly in the retail, e-commerce, and consumer packaged goods (CPG) sectors.
Analytical Skills and Project Management
Anna demonstrates a strong analytical mindset and problem-solving skills, which are critical for addressing complex challenges in data science. She is capable of planning and managing multiple processes and projects simultaneously, showcasing her organizational skills. Her proven track record in working with large datasets further emphasizes her ability to perform exploratory data analysis and mining effectively.