Alina K.

Led and successfully delivered a project on Campaign budget distribution by developing an advanced Fulfilment prediction model that targeted both on-site and off-site Yelp audiences, resulting in a significant quarterly revenue increase. Conducted thorough research on Syndication system behavior patterns and identified areas for improvement in budget optimization, ultimately leading to a remarkable 23% cost reduction in top-tier paying campaign cohorts. Improved the advertisement Auction system by implementing a strategy that showcased relevant ads to users while also providing value to advertisers, resulting in a higher number of clicks. Worked on optimizing the performance of Yelp's revenue-generating products, and also collaborated with other departments to help them better understand their impact on revenue generation.

Developed machine learning models based on gradient boosting and data mining techniques to forecast company's customer churn with a 95% accuracy rate. Performed in-depth statistical analysis on customers and build machine learning to deliver insights about customers of the company. Planned supply and demand actions by building forecasts, improving planning budgets and targets, eventually achieving operational cost reductions by 28% within few month. Build up content Recommendation system to increase conversion rate and number of payments.