Data Scientist, AI & MLOps (mid-level) - Permanent
Role details
Job location
Tech stack
Job description
As a mid-level Data Scientist, AI & MLOps, you'll be part of a growing team building the next generation of predictive, automated, and data-driven systems that influence everything from game design and player engagement to commercial performance and risk management. Our tech stack is cloud-native and Snowflake-centric, enabling fast experimentation and scalable deployment of AI models across the business.
This role is ideal for a hands-on data scientist with experience taking models from concept to production. You'll design, train, and deploy ML models within our Snowflake environment, build automated pipelines, and contribute to an MLOps framework that ensures reliability, scalability, and measurable value. You'll collaborate closely with data engineers, game designers, analysts, and product teams to ensure every model delivers business impact., * Model Development: Design, build, and validate machine-learning models for use cases such as player churn, LTV forecasting, fraud detection, and game optimisation.
- Data Engineering: Work within Snowflake to prepare, transform, and optimise large, complex datasets for modelling and analytics.
- MLOps Automation: Implement CI/CD pipelines, containerisation (Docker), and model-monitoring frameworks to ensure production-grade AI deployment.
- Collaboration: Partner with game, commercial, and finance teams to translate business problems into measurable ML solutions.
- Performance Tracking: Establish KPIs and continuous-improvement loops for models in production.
- Documentation & Governance: Maintain robust documentation, version control, and compliance alignment (GDPR, ISO).
- Innovation: Research and integrate emerging AI tools and generative approaches relevant to iGaming.
- Help build a scalable AI & MLOps ecosystem that powers every aspect of our business
- Work in a creative, fast-paced environment where data directly shapes our games
- Access modern cloud technologies with Snowflake at the core of our stack
- Collaborate with experts who value innovation, learning, and measurable impact
Core Technologies
- Snowflake - Central data platform for modelling, analytics, and orchestration
- Python - Pandas, NumPy, Scikit-learn, TensorFlow/PyTorch
- SQL - Advanced Snowflake SQL and stored procedures
- Docker / Kubernetes - Containerisation and orchestration
- Airflow / dbt - Workflow and transformation automation
- Power BI / Tableau - Visualisation and insight delivery
- Git / GitHub / Bitbucket - Version control and collaboration
- AWS / Azure / GCP - Cloud deployment environments
Requirements
- Strong analytical and statistical modelling foundation
- Experience with data pipeline design and feature engineering in Snowflake or equivalent platforms
- Proven track record of deploying and maintaining ML models in production environments
- Familiarity with CI/CD, containerisation, and cloud compute services
- Understanding of MLOps best practices and model governance
- Ability to translate business goals into technical deliverables
- Excellent communication, documentation, and stakeholder-management skills
- Curiosity, ownership, and a drive for continuous improvement
- Bachelor's or Master's degree in Data Science, Computer Science, Statistics, or related discipline
- Solid hands-on experience in data science or MLOps roles
- Demonstrated experience working with Snowflake, Python, and SQL on production-grade projects
- Experience in iGaming, entertainment, or digital-product analytics is advantageous
