Vladislav Raskoshinskii

Building real-time personalization systems for automotive brands: • Look-Alike Models for Conversion & CTR (Classic ML, Uplift) • Next Best Action Models (Deep Learning, Classic ML) • MLOps for Model & Pipeline Management (MLFlow, DVC, Git) • Models Deployment & Optimization (Docker, Azure) • User Journeys & Marketing Campaigns Optimization (PySpark) • Data-Driven Pipelines Development (PySpark, DataBricks)

Developing and building ML solutions for one of the biggest telecom operator with the main focus on cellular network monitoring. • Developed Anomaly Detection System (Tracks the main cellular network KPIs) • Developed Client Messages Clustering System (Client problems are solved x2-x4 times faster) • Models Deploying and Monitoring in Production • Data Processing Pipelines Building (SQL, PySpark) • Models Optimization and Improvement

Building Data Science solutions to answer business questions • Participation in Pilot Projects (Telecom, Banking) • Collection and Preprocessing of Data • Classic ML Pipelines Building (Regression, Classification) • Hypotheses Proposing and Testing within the Project • ML Models Optimization and Improvement