Senior Data Scientist

Senior Data Scientist About the project: We are hiring for a product-focused iGaming technology company developing advanced real-time personalization solutions for online casino platforms. Their machine learning systems operate directly in production and dynamically shape each player’s experience - including game recommendations, content prioritization, and behavioral targeting - based on live user activity and contextual data. The team builds scalable ML systems that directly influence business performance, user engagement, and retention across multiple clients in a high-load, multi-tenant environment. This is a hands-on role combining modeling, experimentation, and production deployment, working closely with engineering and product teams. Responsibilities: Design, develop, and improve machine learning models for personalization and recommendation systems Enhance and maintain production recommendation pipelines across multiple clients Build models using supervised learning techniques such as regression, classification, and ranking Improve model performance using gradient boosting methods (e.g., LightGBM, XGBoost, CatBoost) and other ML approaches Prepare and process behavioral and transactional datasets for modeling Optimize model training and inference pipelines for performance and scalability Deploy and integrate ML models into production workflows using Airflow and backend services Collaborate with engineers, product managers, and data teams to deliver ML-driven product features Analyze large-scale datasets to generate insights and support product and business decisions Run experiments, evaluate results, and iterate on models to improve personalization effectiveness Contribute to adapting and scaling ML solutions across multiple clients (multi-tenant architecture) Requirements: 5+ years of hands-on experience in Data Science or applied Machine Learning roles Degree in Mathematics, Statistics, Computer Science, or another quantitative field Strong Python skills and experience with data processing tools (Pandas, Polars, etc.) Solid SQL skills and experience working with large datasets Strong understanding of supervised learning methods, especially regression, ranking, and recommendation systems Practical experience with gradient boosting models such as XGBoost, LightGBM, or CatBoost Experience deploying ML models to production environments (real-time or batch pipelines) Experience working with ML pipelines and production systems Understanding of experimentation and statistical analysis (A/B testing, hypothesis testing) Strong analytical thinking and ability to translate business problems into ML solutions Ability to work cross-functionally with engineering and product teams Nice to Have: Experience building or maintaining large-scale recommendation systems in production Experience with Airflow, Redis/Valkey, or FastAPI Experience with Docker and Kubernetes Familiarity with contextual bandits, reinforcement learning, or online optimization methods Experience with AutoML tools Experience working in high-load or multi-tenant SaaS environments Working Conditions: Fully remote position (Europe-friendly time zone preferred) Russian-speaking candidates required Work on a production ML system with real business impact Flexible remote-first culture, with optional office access in Warsaw Benefits include: 21 days paid vacation + 5 personal days Paid sick leave Medical and wellness compensation Sports and wellbeing support Learning and development budget (including language learning support) Equipment provided and workspace setup compensation Team events and company gatherings