Yuliya Porokhnenko

• Clustering application users based on their behavior in the system • System of recommendations for orders for part-time work, solving the problem of a cold start • System for predicting the level of closing of orders for a new client both in new regions and in regions with an existing base of performers • Web application for the analysis of the current base of clients and performers • Setting up and maintaining data processing pipelines using Airflow Stack: Python, SQL, Sklearn, Airflow, Git, Dash, Docker

• Subsystem for forecasting promotions • System for controlling queues in a store based on video analytics • Configuration of cloud services • Web application for forecast monitoring • Telegram bots for timely notification of critical situations, status of the service and status of data transfer • Subsystem for demand forecasting with the subsequent formation of the order to the supplier • Subsystem for monitoring empty grocery shelves based on video analytics Stack: Python, SQL, Sklearn, Flask, Docker