About Scorum
Scorum Group is an international product company in the gambling sector. We specialize in B2B services, delivering two primary products, Aviatrix and ZingBrain AI. 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
We at Zingbrain are seeking a Senior Machine Learning Engineer with deep expertise in recommendation systems, predictive modeling, and production deployments.
You’ll play a key part in developing and optimizing solutions that align with business goals, deliver real-time personalized experiences, and drive impactful results for clients and users worldwide.
As a part of our team you will
- Design and improve algorithms for personalized sportsbook and casino game suggestions.
- Develop models for lifetime value (LTV), churn, and segmentation to help refine retention strategies.
- Ensure machine learning models are production-ready, scalable, and reliable.
- Build systems that enable dynamic, on-the-fly personalization for players.
- Work closely with data engineers to maintain smooth data pipelines for training and deploying models.
- Use A/B testing and experiments to validate your models’ business impact and refine them.
- Work closely with data scientists on algorithms and approaches for business problems and adopt them for clients.
What we expect
Experience
- 3+ years working on machine learning projects, particularly in recommendation systems or predictive modeling.
- 5+ years of experience in software development or computer science.
Core Skills
- Advanced Python skills and familiarity with ML and data processing libraries (TensorFlow, PyTorch, Scikit-Learn, Pandas).
- Proficiency with SQL and large-scale data handling.
- Strong understanding of A/B testing and experimentation approaches.
- Knowledge of MLOps practices, including model deployment and monitoring.
- Experience with workflow orchestration tools like Airflow.
- Familiarity with processing real-time data using technologies such as Kafka, Redis.
- Fluent in Russian and English, both written and verbal.
Nice to have
- Knowledge of reinforcement learning.
How we hire
The decision-making time between stages at Scorum typically spans 3 to 5 business days. However, some interviews or time intervals between interviews for decision-making may take more or less time than indicated, depending on the position, the candidate's specific experience, or other unforeseen circumstances. We are committed to maintaining a transparent and respectful hiring process, ensuring that all candidates are evaluated fairly and equitably. Additionally, we encourage candidates to ask questions at any stage of the process to clarify any concerns or requirements.
Our benefits
Wellness program
- Medical compensation
- Compensation for sports activities
- Well-being webinars and workshops
Work & life balance
- Wellness Day: 4th Friday off monthly
- Remote work
- 21 working days of vacation
- 5 personal days per year
Professional development
- English speaking club
- Language learning bonus €150 per month
- 80% paid professional employee training
- Provided tech equipment
Extra advantages
- €150 for the arrangement of the workplace
- Bonuses for significant events and additional personal days if necessary
- Offline and online company parties and team buildings
Why work at Scorum?
Joining Scorum means becoming a part of a company that prioritizes steady progress, efficiency and innovation. Our growth is consistent and thoughtful. We avoid sharp leaps in employee expansion, as we're striving to ensure the correct establishment of processes and smooth development. This approach allows us to maintain a stable environment and makes Scorum a standout place to advance your career in the gambling industry.
Our product portfolio
Aviatrix, crash-game with NFT-based rewards, gained global traction and won industry awards last year
ZingBrain AI personalizes casino content using machine learning to boost revenue
Blockchain platform for global sports fans, providing diverse multilingual content