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What makes us proud?
- In just two years, we’ve launched two successful mobile games worldwide: Playdoku and Colorwood Sort. We have paused some projects to focus on making our games better and helping our team improve.
- Our games have been enjoyed by over 45 million players worldwide, and we keep attracting more players.
- We’ve created a culture where we make decisions based on data, which helps us grow every month.
- We believe in keeping things simple, focusing on creativity, and always searching for new and effective solutions.
- Genres: Puzzle, Casual
- Platforms: Mobile, iOS, Android, Social
130+ employees
Key Responsibilities
- Build and maintain ML for product and marketing teams
- Develop predictive systems for personalization, recommendations, and dynamic game content
- Automate data workflows and create reliable, scalable ML pipelines from feature engineering to deployment
- Monitor model performance, detect drift, and ensure ongoing accuracy and stability of ML systems
- Partner with Product, Marketing, and Engineering to integrate ML solutions into live games and operational workflows
- Own DS/ML projects end-to-end: from defining the problem to production deployment and iteration
- Share knowledge, conduct code reviews, and promote best practices across the data team
- 4+ years of experience in Data Science or ML, with a track record of delivering production models (2+ years in gamedev or consumer apps businesses)
- Strong background in statistical modeling, forecasting, and machine learning
- Advanced programming skills in Python or R (pandas, numpy, scikit-learn, PyTorch/TensorFlow or tidyverse, caret, mlr), writing clean and maintainable code
- Excellent SQL skills, confident with large-scale datasets and cloud data warehouses (BigQuery, Snowflake, Redshift)
- Experience deploying, monitoring, and maintaining ML models in production environments
- Strong problem-solving mindset, able to translate business and product goals into ML solutions
- Clear communicator who can explain complex models and systems to both technical and non-technical teams
- Passion for gaming and curiosity about player behavior
- Experience building user-level LTV forecasting models
- Background in recommender systems, personalization, or contextual bandits
- Familiarity with MLOps practices and tools
- Experience with ETL/orchestration frameworks (dbt, Dataform, Airflow)
- We run on GCP — experience with BigQuery, Vertex AI, Pub/Sub, and Cloud Run/Functions
- 100% payment of vacations and sick leave [20 days vacation, 22 days sick leave], medical insurance.
- A team of the best professionals in the games industry.
- Flexible schedule [start of work from 8 to 11, 8 hours/day].
- L&D center with courses.
- Self-learning library, access to paid courses.
- Stable payments.
CV review → Interview with TA manager → Interview with Head of Analytics → Final Enterview → Job offer
If you share our goals and values and are eager to join a team of dedicated professionals, we invite you to take the next step.
Key Skills
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