Роман Васильев Email & Phone Number

• Formed team of 5 DS/DA• 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)• Created CDT-centered categorical review process. Result: ~50 new SKUs per month, ~70% of them are moving to main category matrix

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

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 consultants and category managers on creating promo recommendations.

Москва, Россия

• 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. increased project revenue by more than 12%.• 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. Developed models to detect communities using telecom data (households, families, colleagues). These data allowed us to obtain significant quality gains in most personalization projects• 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)

Прикладная Математика И Информатика

Education record

An intensive structural thinking and career building 21-day education course (more than 60 hours of study and more than 80 hours.