Vitalii Korneev
About Vitalii Korneev
Vitalii Korneev is a Research and Analytics Manager at Mail.ru Group, with a background in data analysis and applied mathematics. He has a proven track record of improving predictive model accuracy and minimizing losses through effective reporting.
Current Role as Research And Analytics Manager
Vitalii Korneev currently holds the position of Research and Analytics Manager at Mail.ru Group, where he has worked since 2020. In this role, he focuses on data analysis and research methodologies to support business decisions. His responsibilities include overseeing analytics projects and ensuring the effective use of data to drive insights and strategies.
Previous Experience at Mail.ru Group
Prior to his current role, Vitalii Korneev worked at Mail.ru Group in various capacities. He served as a Middle Data Analyst from 2019 to 2020, and as a Junior Data Analyst from 2018 to 2019. During his tenure, he developed an auto-updating report on new growing games using R and implemented the 'Prompter' recommendation system, which resulted in a 5% increase in profits.
Experience at ROSST
Before joining Mail.ru Group, Vitalii Korneev worked as a Data Analyst at ROSST from 2016 to 2017 in Moscow, Russian Federation. In this role, he contributed to minimizing losses in purchases by 10% through the creation of informative reports that helped understand changes in forecasts, metrics, and features.
Education in Applied Mathematics and Computer Science
Vitalii Korneev studied at Lomonosov Moscow State University (MSU), where he earned both a Bachelor's degree and a Master's degree in Applied Mathematics and Computer Science. He completed his Bachelor's degree from 2012 to 2016 and his Master's degree from 2016 to 2018, equipping him with a strong foundation in quantitative analysis and computational techniques.
Achievements in Predictive Modeling
Throughout his career, Vitalii Korneev has made significant contributions to predictive modeling. He improved the accuracy of predictive models to 87% by introducing a probabilistic model for attributing lost users. This enhancement demonstrates his capability in leveraging advanced analytical techniques to drive business outcomes.