Data Scientist driving detection and mitigation of fraud across audio verticals on our platform. Collaborating with data scientists and ML engineers to ensure fair engagement and accuracy for users and creators.
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
Experience level
Salary
Not specified
Degree requirement
Tech skills
Location requirements
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