Integration of Automated Machine Learning Model in Sales Support

• Developed an automated Python Machine Learning model that provides post-evaluation for sales support programs and takes mutual cannibalization into account.
• Organized and led an ETL developers team that built Avon Russia's Cloud Data Warehouse, the only data source with consolidated and verified business data for operational analytics.
• With a team of ETL Developers Rebuilt Russian data instance of Global DWH in Snowflake with attached data flow interfaces.
• Initiated, developed, and implemented new Representative discount system and performance tracking dashboard in Tableau to promote productive sales behaviour
• Initiated and performed audit of existing business planning processes, suggested ways to improve demand forecasting accuracy
• Initiated and performed series of strategic analysis on pricing, average order, representatives’ costs and benefits to understand causes behind current business performance and highlighted possible business solutions to the top management and enabled more accurate sales predictions.

As part of my role at Time Research & Innovation, I Ied creation of World Health Aid (WHA), a multilingual real-time health advice platform designed to support disadvantaged individuals. WHA is a comprehensive solution that facilitates telemedicine services, bridging the gap between healthcare providers and underserved populations. It combines live patient and clinician-facing decision support systems, offering a range of paid and free services, including self-diagnosis screening through video and voice chat, multilingual instant translation, voice-command symptom search, real-time messaging, and secure record keeping.

• Gathered a team of BI Analysts and Developers from the scratch
• Created a data warehouse prototype using Qlik Sense and built a full commercial business reporting system from the ground
• Complete evaluation of the company's business reporting system, including financial reporting. Sources of financial losses and inefficiency have been identified and quantified.
• Provided recommendations to the operations office on sales enhancement activities and monitored implementation, which resulted in a significant revenue impact.
• Built demand forecasting model using XGBoost Regression

Over a three-year period, we worked closely with one of Russia's largest banks to successfully establish a robust AI monitoring system. This system operates with precision to swiftly address system failures by pinpointing their root causes and making well-informed decisions. The model expanded the scope of forecasted indicators to a total of 50,000, achieving an 85% reduction in false positive alerts. It also delivered a 20% improvement in precision compared to previous methodologies.

Led a team to develop an AI monitoring system that was capable of detecting anomalies in various business indicators. By closely working with one of Russia's largest banks over a span of 3 years, we designed and implemented an advanced backend system dedicated to the detection of anomalies across a wide spectrum of critical business metrics. This system significantly decreased the time and effort previously invested in manual incident detection and enhanced operational efficiency.