Data Scientist

Easybrain is looking for a Data Scientist to join our Business Intelligence team. Our ML models run in production, powering LTV prediction and user acquisition optimization across a portfolio of games with billions of installs. Your focus will be on building new ML systems for ads monetization and game personalization from the ground up. This is a hands-on, end-to-end role focused on improving business metrics. You will own your models from problem framing through research, production deployment, validation, and post-launch iteration. Responsibilities:- Researching and developing ads monetization optimization (floor pricing, ad load balancing) - an open research problem: from studying the underlying dynamics and simple heuristics to ML models and potentially RL; - Predicting LTV and other key user metrics using large-scale behavioral data: improving forecast accuracy through new modeling approaches, data signals, and features; - Building in-game personalization systems: difficulty and content management; - Validating models through A/B tests in collaboration with the analytical team and bringing them to production. Tech stack: Python - you’re free to choose whatever ML tools fit the task best (PyTorch and LightGBM are in production today); ClickHouse, PostgreSQL, Airflow, MLflow, Docker. Requirements:- Experience in predictive modelling and deploying ML models to production: framing an open problem, exploring the data, building baselines, and iterating towards an ML solution; - Strong knowledge of Python and hands-on experience with the modern ML stack; - Profound understanding of statistics and machine learning; - Experience in reinforcement learning, recommender systems, ad tech, or mobile games is a plus; - B2+ level of English; - Fluent Russian is required. Benefits:Besides the engaging tasks, support from experienced colleagues, challenge, and drive, we offer: - Full support in relocating to countries where our offices are located; - High-end market salary with performance bonuses; - All needed equipment; - Regular company events and monthly Friday meetings; - Social benefits (private medical cover, sports reimbursement, etc.); - Paid vacations, sick days; - English, Greek, and Polish online language classes; - Reimbursement for education and professional development.

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