Data Scientist, Ai & MLOps (Igaming)

TL;DR

Data Scientist, AI & MLOps (iGaming): Design, train, and deploy ML models within a Snowflake environment, building automated pipelines and contributing to an MLOps framework. Focus on translating business problems into measurable ML solutions and integrating emerging AI tools relevant to iGaming.

Location: Hybrid in any of the following - UK (London), Poland (Warsaw), Malta (Ta' Xbiex), Isle of Man.

Company

hirify.global designs games that blend creativity, data, and technology to deliver unforgettable player experiences.

What you will do

• Design, build, and validate machine-learning models for use cases such as player churn, LTV forecasting, fraud detection, and game optimisation.
• Work within Snowflake to prepare, transform, and optimise large, complex datasets for modelling and analytics.
• Implement CI/CD pipelines, containerisation (Docker), and model-monitoring frameworks to ensure production-grade AI deployment.
• Partner with game, commercial, and finance teams to translate business problems into measurable ML solutions.
• Maintain robust documentation, version control, and compliance alignment (GDPR, ISO).
• Research and integrate emerging AI tools and generative approaches relevant to iGaming.

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.
• Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, or related discipline.

Nice to have

• Experience in iGaming, entertainment, or digital-product analytics is advantageous.

Culture & Benefits

• 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.
• Work in an environment that’s built around trust, collaboration, transparency and accountability.
• Opportunities, flexibility and creative freedom.