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.