Iuliia Koshkareva

Developed machine learning algorithms for a variety of fields: bank risks, sport analytics, cybersecurity and employee experience. Projects: * Employee feedback analysis with text analytics (topic modeling, sentiment analysis) * Development of machine learning approach to match candidates with jobs applying semantic embeddings * Optimization of a call center performance using machine learning based on socio-demographic characteristics and audio features extracted from real calls

Solved data analysis problems with neural networks. Data processing with pySpark: replacing missing values, highlighting data points across visualizations. Feature selection with shap values. The full stack of working with the model - from data collection to evaluation of results and visualization. Projects: * Development of a model for predicting game events in real time * Development of a clustering model of the clients

Solved data analysis problems with machine learning algorithms. Worked with trend identification, data seasonality, noise detection. Deployed the interactive web-application interface with SQL database on Plotly Dash framework. Projects: * DNS tunnel detection model * Typosquatting detection model * The analytical system of car logs for the Russian Circuit Racing Series

Implemented the rules of normalization and correlation in the MaxPatrol SIEM system to identify DDOS attacks. The created rules are included in the knowledge base of the MaxPatrol SIEM system