Senior Data Scientist

We're an international product company in the gambling sector. ZingBrain AI personalizes casino content in real time using advanced machine learning to help operators boost player engagement, retention, and revenue. Our mission is to empower gambling businesses worldwide by streamlining operations and elevating player experience with innovative features.

• 5+ years of experience in data science
• Degree in a quantitative field (e.g., Mathematics, Statistics, Computer Science)
• Proficiency in Python, SQL, and data manipulation tools (Pandas, Polars)
• Strong engineering skills to design, build, and maintain scalable ML solutions including observability through metrics, logging, alerting
• Knowledge of Docker, Kubernetes
• Hands-on experience with supervised ML techniques (regression and ranking) using XGBoost, LightGBM, CatBoost, or neural networks
• Experience with feature engineering, model evaluation (AUC, NDCG, MSE, uplift metrics), personalization or recommendation systems
• Proven experience deploying ML models to production for near real-time or batch processing
• Solid knowledge of statistical methods such as A/B testing and significance testing

Nice to have:

• Production experience with large-scale recommendation systems
• Production experience with Airflow, Valkey/Redis, FastAPI
• Familiarity with contextual bandits or reinforcement learning for online optimization
• Familiarity with AutoML

• Develop ML-driven features for casino games using supervised learning (regression, ranking, classification)
• Maintain and enhance existing recommendation systems including model enhancement with gradient boosting methods, data cleaning, preprocessing, and optimization of training and inference pipelines
• Integrate ML models into Airflow pipelines in a multi-tenant environment
• Adopt and configure solutions for different clients (tenants)
• Collaborate with cross-functional teams including data scientists, engineers, product owners, designers, and researchers
• Analyze large datasets to extract actionable insights
• Propose, implement, and evaluate machine learning approaches with close cooperation with Product Owner(s)
• Influence product strategy through research and experimentation