Summary
Pavel Irmatov is a data scientist with nine years of professional experience and seven years focused on data science, blending machine learning, discrete optimization and high-load backend engineering. He has delivered production-ready solutions from cost-optimization and route planning to bilingual TTS research at Yandex, and has hands-on experience deploying models and building robust data pipelines. Pavel combines deep algorithmic skills (LP, MIP, local search) with practical ML expertise (PyTorch, XGBoost, CatBoost) and a history of squeezing measurable value—his optimization work once reduced printing production costs by about 11%. He has led teams and coordinated projects for over five years, bridging business stakeholders and engineering, and is comfortable across databases and distributed infrastructure (Cassandra, Elasticsearch, Redis, RabbitMQ, AWS). Notably, he pairs research-oriented tasks like dataset filtration for accent handling in TTS with pragmatic engineering—producing both experiment design and production deployment. Based in Saratov, Russia, he brings a rare mix of optimization-first thinking and production-grade software craftsmanship.
9 years of coding experience
16 years of employment as a software developer
midle school number 22 city of Engels
Specialist, Computer science, Specialist, Computer science at Саратовский Государственный Университет им. Н.Г. Чернышевского
English, Russian