Head of analytical tools development team

July 2022 - now

Yandex.Lavka, one of the largest e-grocery platform in Russia

• Formed team of 4 DS and 3 DA
• Created CDT-centred categorical review process, based . As a result, ~50 new SKUs per month in category matrix, ~70% of them are moving to main category matrix
• Developed new metrics (such as space efficiency, repeat rate, retention, etc.) and dashboards based on them for category managers
• Organized and calculated AB tests on stores and user levels
• Lead BI-reporting of commercial analytics (autoorder, pricing, assortment) at the company level
• Organized product matching process: developed auto-matching model (using NLP approaches)

Lead Data Scientist

July 2021 - July 2022

Magnit, the largest retail company in Russia

• Created team of 3 DS, 4 BA and 2 DE
• Managed team backlog, organized developing process and ad-hocs process
• Implemented culture of using CDT. Developed approach to CDT creation and assortment optimiztion process based on it
• Developed user-based metrics and integrated it to internal assortment optimization system and BI system
• Demand forecast model for assortment optimization

Senior Data Scientist

December 2020 - July 2021

Magnit, the largest retail company in Russia

• Worked on the development of a tool for evaluating the effectiveness of past promos • with expected value more than 1 billion rubles.
• Developed several modules: Losses, Markdown, Pull Forward, Footfall.
• Worked on developing a demand forecast model to evaluate promo.
• Worked with BCG consultans and category managers on creating promo recommendations for Fresh categories.

Data Scientist

December 2018 - December 2020

MegaFon, the largest telecommunication company in Russia

• Telecom credit products improvement project
  Created process of using ML models in credit project with more than 3 million users: developed default model and tariff policy strategy based on it
• Anti-Downsell project
  Created segmentation and several approaches to detect downsell in customer groups
• Customer data upgrading project
  Created ML-models oriented on receiving extra customer properties - gender, age, psychotype on more than 70 million customer base
• Managed the interns group
  Led the interns groups up to 8 members, supervised their projects, organized the courses of using Big-Data tools in industry (SQL, HIVE, Spark, etc)

Master's degree

2020 - 2022

Moscow State University, Faculty of Computational Mathematics and Cybernetics

Scientific interests: graphs analysis and representation learning

Bachelor's degree

2016 - 2020

Moscow State University, Faculty of Computational Mathematics and Cybernetics Department of Mathematical Statistics

Thesis: Representation learning on large graphs in telecommunication via deep learning methods

Additional Education

• Changellenge Winter School (top-1 of participants)
  February 2020
• Course “Practical Machine learning”, “Practical Big Data” by BIGDATA TEAM
  2019
• Deep Learning School by Moscow Institute of Physics and Technology
  2019