Implementing Universal AB Testing and Web Analytics Across Platforms

• Developed a universal platform for AB testing.
• Led the setup of a web analytics system from scratch across multiple websites and a mobile application, including change monitoring and business reporting.
• Built a team of marketing analytics to assess the effectiveness of advertising placements of various partners on the site.

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.

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.

I coordinated a team in the development of two distinct automated incident detection models, which yielded substantial improvements in incident detection times, reducing them by an impressive 5 to 15 minutes. These models played a pivotal role in streamlining processes and optimizing the bank's operations.