Senior Data Scientist
About the role
About Us
We're an international product company in the gambling sector. ZingBrain AI personalizes casino content in real time using advanced machine learning, helping operators boost player engagement, retention, and ultimately revenue. Our mission is to empower gambling businesses worldwide by streamlining their operations and elevating the player experience with groundbreaking features.
Who We're Looking For
At Zingbrain, we build real-time personalization systems for iGaming platforms. Our models operate in production, influencing what each user sees — from game recommendations to sportsbook event suggestions — based on live behavioral, transactional, and contextual data. We’re looking for a Senior Data Scientist to join our team and help us in the following areas:
- Develop ML-driven features for casino games using supervised learning (regression, ranking, classification)
- Maintain and enhance the existing recommendation systems in production, including:
- Model enhancement using gradient boosting methods
- Data cleaning and preprocessing
- Pre- and post-processing workflows
- Optimization of training and inference pipelines
- Integration of ML models into Airflow pipelines in a multi-tenant environment
- Adopt and configure the solution for different clients (tenants)
This is a hands-on role involving modeling, experimentation, and close collaboration with engineering and product teams in a high-load, real-time environment.
As a Part of Our Team You Will
- Collaborate with cross-functional teams of data scientists, engineers, product owners, designers, and researchers to ensure project success
- Analyze large datasets to extract actionable insights that inform product decisions
- Propose, implement, and evaluate machine learning approaches to solve business problems, work closely with Product Owner(s)
- Maintain and adopt the current recommendation solution in multi-tenant environment
- Influence product strategy through research and experimentation that deepens understanding of how product features, platforms, and promotions affect user behavior