Leonid Danilchenko

Spearheaded the successful launch of Datalore Cloud, a SaaS version of the on-premise solution, contributing 25% of new revenue.

Led cross-functional collaboration with engineering, UX, marketing, and sales to achieve 2-3x Year-over-Year revenue growth and accelerate user adoption.

Delivered multiple beta releases for new IDE service integrations, leveraging customer research and market insights to prioritize development.

Conducted over 20 enterprise customer interviews, directly shaping the strategic direction for developer tools and cloud-based enterprise solutions.

Optimized ML-powered Face Swap & Lens quality, enhancing realism and engagement, resulting in over 30 viral lenses.

Drove growth initiatives, including onboarding improvements and content creation, significantly increasing user engagement.

Launched and analyzed A/B tests for lens distribution and discovery, optimizing engagement across Snapchat's AR ecosystem.

Collaborated with sales and partnerships teams to design custom ML-powered lenses for paid special projects, supporting branded campaigns and monetization efforts.

Drove migration from monolith to microservice architecture, tripling feature release velocity and enhancing platform scalability for millions of users.

Enabled the rapid launch of 3-5 new applications (e.g., Revive & Restyle) by leveraging existing AI infrastructure, facilitating experimentation with new audiences and product ideas.

Collaborated with ML, data, and mobile teams to enhance AI-driven face-swapping models, improving realism and processing speed.

Contributed to Reface.ai achieving #1 ranking in the Apple App Store & Google Play Store across multiple countries, maintaining top position for several weeks.

Led the development of an internal AI-powered Data Science tool, automating buyer workflows and improving warehouse stock realization and demand forecasting during COVID-19.

Drove MLOps transformation, implementing CI/CD pipelines for ML models that cut deployment time and improved collaboration for 10+ data scientists and engineers.

Collaborated cross-functionally with supply chain, engineering, and data science teams to integrate AI-driven inventory optimization and sales forecasting models.

Presented key AI initiatives to VP-level executives, directly shaping the company's ML strategy and adoption roadmap.

Developed and implemented a process for evaluating search quality, achieving an increase in search relevance that directly influenced revenue growth.

Led a team of 5 Analysts/Data Scientists, mentoring junior talent and organizing a Bootcamp program for new hire onboarding.

Co-developed an ML-driven auction model for a location-based ad format, pioneering geo-specific advertising solutions within Yandex Maps & Navigation.

Pioneered an ad format that became an industry benchmark, later adopted by competitors like Waze and Google Maps.

Built and scaled analytics infrastructure for a sales department growing from 0 to 200 people, automating KPI dashboards and CRM insights to support data-driven decision-making.