Data Manager managing data analytics consulting projects at PwC. Collaborating on data - driven solutions and overseeing implementation while maintaining client relationships.
About the role
- Mid-level Data Scientist in AI & MLOps at Push Gaming. Developing predictive systems and ML models for enhancing game design and player engagement.
Responsibilities
- 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
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.
Benefits
- Health insurance
- Professional development opportunities
- Opportunities for growth and flexibility
Job title
Job type
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Not specified
Degree requirement
Tech skills
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