1) Team lead of DWH development: - Organization of data enrichment process extracting data from different systems and micro-services - Management of ETL process - Data governance - Estimation and regular monitoring of data quality - MetaData management. Methodology of object description for all sources presented in the system 2) Data Visualization: - Reporting in Tableau BI system and Grafana - Control and optimization of all the reports used overall departments of the company - Prioritization process for all RFI from different business departments 3) DataMining and Machine Learning practices - API implementation in production systems (front/back-end) - Forecast of propensity to buy and client segmentation - Personal recommendation system for sorting offers in the marketplace based on client behavior and interests

1. Support and development of BI reporting system 1.1. Design of new reports according to RFI 1.2. Technical support of existing reports 1.3. Implementation of new data sources for reporting and analysis 2. Full cycle of sales-funnel optimization at all the stages using predictive models (decision trees, neural networks, regression, clusterization) 2.1. Robust predictive models for conversion prediction based on behavioral patterns of clients 2.2. Fast deployment of new analytical services to production OLTP servers 2.3. Optimization and quality control of predictive models

1. Creating the set of price-plan Identification of key differentiators of company price-plans in comparison with existing products of competitors. Development of price-plans for different usage-profiles and their margin estimation. 2. Estimation of financial indicators of project payback Financial modeling of the project (payback, breakeven, irr). Presentation of the result to investors with plans for project’s funding. Prioritizing the allocation of funds in the following areas: network construction, IT, marketing. 3. Development of the concept for launching the operator Selection of the target audience of the company's clients, managing tenders for the selection of the creative agency. Distribution of the budget for promotion through channels and major Internet sites. 4. Prioritization of the network construction Selection of Moscow districts with the largest penetration of the target audience of the company. Planning of indoor network construction in places most frequented by the target audience. 5. Planning of purchases of subscriber equipment and SIM cards Analysis of Russian device market (smartphones and tablets) that support the standard of the TDD-LTE network. Forming the catalog of the company's online store, pricing of user devices.

1. Client analytics • Insights for lifecycle of device usage causing change of profitability and traffic consumption. Tracing triggers that in the best way predict upgrade (purchase of more expensive smartphone) and downgrade (purchase of cheaper smartphone) of client’s device. Appling these insights in the real business we could change our strategy of device promotion and launch targeted campaigns in time for those who intended to change their smartphones. • Media buying optimization based on deep analysis of subscribers web navigation. Determining for each subs group (high/medium/low-value) and product category (tariff, added service, price-plan discount) most relevant web-sites to place a product advertisement. As a result the company could make better targeting of heavy mobile-internet users. • Mass-market segmentation on basis of intersection of different data types (behavioral, geo-location, life-style, psychographic). Determining robust usage segment profiles and development of marketing strategies for each segment. Evaluation of revenue growth opportunity in case of different marketing segment scenarios. The result of this project was applied almost for all the core-business activities (tariffs, new products promotion, monobrand offices relocation, etc.) 2. Financial forecasting and simulation • Elaboration of long-time revenue forecasting model considering different prospects of new SIM-cards volume, sales distribution by channels, product-mix by channels, subs activity dynamics. This model gave us a global vision how to spend our budget for new SIMs smarter than before. • Financial modeling of B2C subs transition to bundle tariffs (tariff group «ВСЁ!»). Estimation of churn loss and usage boost for each price plan configuration. Using this model we could evaluate our loss and benefits when subs migrate on bundle tariffs from flat price-plans, and calculate optimal pricing parameters. 3. Big data for out-of-core businesses The main idea consists in development of complex knowledge of client to be offered for sale to big B2B companies. In my responsibility was a full scope of managing analytical activities for developing such products. The most important sectors/industries involved as potential purchasers: • Banking sector. Improving bad-borrower scoring cards by adding some telecom specific parameters (geo-location, mobile usage frequency, etc) • City infrastructure planning. Road-building planning taking into account geo map reports about traffic intensity, population density in the regions of the city, migration to other cities. • Retailers/FMCG. B2B clients were interested in life-style patterns of their customers and in their geo-location (location of home/job/leisure for mobile advertising). This direction of new businesses is still at the stage of coming-to-be (mostly in form of prove-of-concept), but shows already very encouraging result and seem attractive for B2B clients

1. Big data for out-of-core businesses • Project management in client data monetization:  Predictive models of client churn  Scoring models of clients susceptible to buy new value-added services  RFM-scoring of behavioral characteristics of client base • Implementation of partnership projects related to profound analysis of client transactional data:  Collaborative projects with banks consisting in analysis of clients’ reliability and detection of “bad” debtors on the base of merging telco and banking data  Projects with FMCG companies with the purpose of getting lifestyle and payment patterns of client behavior 2. Development of analytical instruments for decision making and marketing automation: • Federal client segmentation on the base of transactional data for optimization of targeted-marketing campaigns • Implementation of the system evaluating efficiency of advertising budget distribution 3. Management of requirements to business support systems: • Implementation of the system managing all business requirements to the billing • Management of datawarehouse development according to principal needs of business

1. Management of requirements to the principal business support systems: • Communication with key-business users concerning their needs of new functionalities • Consolidation and prioritization of requirements to billing systems, initiated by regional branches 2. Control of the budget for development of analytical systems in regions: • Annual budget planning with the object of developing analytical systems and local BI-initiatives

1. OLAP-system for KPI analysis and reporting: • Implementation of the system in regional subsidiaries and branches • Collaboration with IT-integrators apropos of development and system audit • Control of data consistency in the system • SLA development of deadlines for loading data in the system • Participation in requirements specification for developers • Implementation of web-interfaces to the system (dashboards, reports) • Organization of software purchases for system developments • Education of developers, administrators, end-users 2. Internal CMS WEB-portal: • Implementation of the system according to business requirements • Development of new functionalities and services 3. Analytics: • Mathematical models for efficiency evaluation of the key business directions • Analysis of federal campaigns and products promotion 4. Reporting: • Regular regional markets monitoring • Preparation of consolidated reports for top-management • Plan/fact analysis of KPI