Summary
Anton Lebedevich is a Data Analytics Engineer with 17+ years of software experience and a decade-long focus on data and ML engineering, currently building scalable pipelines on AWS using Python and Spark. He moves projects from problem definition through data collection, modeling and production deployment, with strengths in ETL, forecasting, anomaly detection and AB-testing. His background in applied mathematics and early career in embedded and high-throughput backend systems gives him a rare blend of low-level performance tuning and high-level analytical modeling. Notable achievements include migrating terabytes from on-prem Hadoop to AWS, implementing 15 new AB-test metrics, and building demand-forecasting pipelines for thousands of SKUs. Comfortable leading small distributed teams, he also introduces engineering best practices—code reviews, CI workflows and reproducible deployments—to data organizations. Based in Yerevan, he relishes digging into performance monitoring data to find the non-obvious explanations behind system behavior.
17 years of coding experience
12 years of employment as a software developer
Engineer, Applied Mathematics, Engineer, Applied Mathematics at National Research Nuclear University MEPhI (Moscow Engineering Physics Institute)
English, Russian