Moscow, Central Office – Corporate Investment Business - Intelligence control system - Artificial intelligence team)- Developed an ML model for predicting customer flow at Multifunctional Service Centers, reducing queue waiting time by 20%. The forecast covers up to 2 months ahead, with half-hour intervals. MAPE < 18%. - Achieved a nearly 80% reduction in the second-month churn rate of new sales trainees by analyzing data on their behavior in the onboarding system and interactions with the gamification system, identifying patterns, and providing insights to adjust gamified onboarding scenarios.- Focused on Classic ML, Time Series and NLP. The 360-degree evaluation highlighted my business acumen, clear interpretation of results, and visualization of reports for stakeholders, as well as the ability to identify errors and optimize 'other people's' code (legacy).

I implemented several decisions:- Computer Vision. I built a CNN model of classifying cars by photos for car resale department. In the project I used: transfer learning on Xception, EfficientNet[B0, B3], optimizers (Adam, Adamax Nadam), callback (EarlyStopping, LearningRateScheduler), fine-tuning, Batch-normalization with baes off on the previous layer, Test Time Augmentation. Main stack: tensorflow, keras, albumentations. Created a CNN model for classifying cars based on photographs,increasing the conversion rate from website visits to trade-in deals by nearly 75% through initial online valuation based on photos.- Parsing+ML. I have parsed all the ads from auto.ru website in Moscow and built a model of forecasting a market value for a car based on its characteristics for car resale department. I determined that MAPE metrics is inconsistent in regard to evaluation of the model performance and introduced additional metrics. I used the following feature selection methods for the project (correlation matrix, ANOVA F-test, Student t-test, feature_importances_RF + noise), sklearn(LinearReg, RandomForest, GradientBoostingReg, ExtraTreeReg, BaggingReg), blending. Scraped all listings from auto.ru in Moscow and developed a car market value prediction model, doubling the speed of trade-in car acceptance from 1 hour to 30 minutes and increasing net profits by 12%. The model provided managers with optimized pricing recommendations, while allowing them to make independent pricing decisions.

- Obtained an academic degree in teaching from a college in Israel (in Hebrew)- Successfully completed an internship at the school during the academic year (in Hebrew)- Licensed as a high school math teacher after completing qualification evaluation and validating the diploma of higher education as well as passing language proficiency exam in Hebrew- Mentor of the students’ team in the robotics competition "First Lego League"Only 4 out of 22 participants in the teacher training program were able to complete it successfully from the attempt be licensed as teachers in Israel

(Procter & Gamble Distribution Management System CJSC (P&G DMS CJSC) in West Siberia)- The Company’s sales operations management in 14 cities of West Siberia - Novosibirsk, Kuybyshev, Tomsk, Barnaul, Rubtsovsk, Slavgorod, Biysk, Omsk, Tyumen, Kurgan, Surgut, Nizhnevartovsk, Noyabrsk, Sovetsky- Sales Department operations management (I had 3 Department Directors in direct supervision: Marketing and Advertising Department (including BTL full service company) and the Company’s Proprietary Business Departments in professional and FMCG lines)- Fulfillment of sales plan within the assigned territory in accordance with the Company’s standards- Participation in quarterly and annual meetings of P&G distributors representing the Company’s interests - Development of the Company’s Proprietary Business (CPB)DMS became the best P&G distributor of the year. I ensured the successful implementation of “The Baikal” federal project pertaining to logistics transparency of P&G distributors with regards to the Sales Department. I organized two visits of the P&G top team on the Company’s premises. DMS also took the first place in the Priorities of the Year contest and according to Nielsen, displayed Russian average outstripping growth in market shares in major product categories compared to the previous year.Acquisition of a distributor on the territory of Tuymen region , Khanty-Mansiysk Autonomous District and Yamalo-Nenets Autonomous District.

B2B, advertisement placement in city information guides containing city maps; B2C, creating user-friendly information guides with city maps) - Operations management of the Company’s Regional Network - 20 cities in Russia and Ukraine (10 branches and 10 franchise partners)- Operations and strategy management of Commerce Department (Marketing Department (10 employees) and Sales Support Department (6 employees))- Development, implementation and maintaining standards of Regional Network operations in sales and marketing- Fulfillment of sales plan and development of the Regional Network - Monthly performance evaluation of the branches in terms of commerce and marketing- Organizing support and development of CRM system tailored to the Company’s objectivesI developed and implemented a new remuneration system for employees of the Department. I resumed planned staff assessment of the Commerce Departments of the branches. The Sales Development Group was allocated to the Company’s Training Center for good performance. I ensured high accuracy of monthly sales planning.

- Analyzed and executed KPIs while managing orders and preparing territories for executive visits, demonstrating strong analytical skills and consistently meeting performance targets- Mentored a team of five client account managers, providing training on route sales techniques and ensuring the achievement of monthly sales targets