Give lectures on data science in various companies as an invited expert. For example: read lectures for top-managers of Russian Central Bank.

Developing blockchain and decentralized exchange using Rust and Substrate. Developing custom Substrate pallets. Made architecture of cross-layer yield DApp.

Course Author: «Monitoring and Model Quality Management». Mentor of the advanced ML Engineer track.

Author and lecturer of Machine Learning and Python courses for children in grades 10 – 11

ML experience: Built stickiness model for evaluating the lives of customer deposits. The model was built as a stack of 2 gradient boosts. The model is orchestrated using DVC and Airflow. All metrics are displayed in MLFlow and a dashboard is drawn in Grafana. The ci/cd process has been set up for rolling out new versions. Docker-compose backend built. Also helped to built deposit pricing model. The model is designed using an uplift (T-Learner). And also built a model for portfolio prediction. The problem was solved as forecasting a time series. Data Engineering experience: Engaged in transfusion of data from various database management systems, such as postgresql, mysql, GDWH into HDFS using Airflow and Spark. Created various data marts using hive and pyspark. Analytics experience: Conducted analytical calculations on various CIB products. Built an advanced BI system using Tableau.

Analytics experience: Analyzed accounting systems and financial transactions in order to identify cases of fraud for large companies in the industrial, banking sectors, as well as retail. Developed a high-level business process optimization plan for a major diamond manufacturing company (Alrosa). ML experience: Built a model to predict the loss of value of a diamond at different stages of its processing. The model was built for a major diamond manufacturing company (Alrosa).