Machine Learning Scientist

Metica; London; Hybrid; GBP 50,000 - 90,000

Job description

The Role

We’re looking for an experienced ML Scientist to join our team and help us build, refine, and scale the AI-driven models that power Metica’s cutting-edge personalization and optimization solutions. In this role, you’ll leverage your expertise in machine learning, statistical analysis, and software development to extract insights from data, develop impactful models, and drive actionable recommendations for some of the world’s leading gaming studios and publishers.

This is an exciting opportunity for a hands-on data scientist who thrives in a fast-paced startup environment, loves solving complex problems, and is passionate about gaming and data-driven technology. This is an in-office role based in London, with the flexibility to work from home one day per week.

You Will

• Design, build, and refine machine learning models to optimize player engagement, retention, and monetization.

• Collaborate with product, engineering, and data teams to align technical solutions with business goals.

• Perform exploratory data analysis to uncover actionable insights from large datasets.

• Stay updated on the latest advances in AI and machine learning, and identify opportunities to incorporate them into Metica’s platform.

You Need

• 5+ years of experience in machine learning or advanced statistical modelling.

• Expertise in one of: recommender systems, reinforcement learning, contextual bandits, causal ML or sequence modelling.

• Proficiency in Python and at least one ML framework, such as Tensorflow, PyTorch or JAX.

• Ability to easily communicate complex technical ideas to non-technical audiences.

• Familiarity with manipulating and analyzing large datasets using SQL or other related technologies.

Bonus Points For

• Experience with marketing technology or ad monetization platforms.

• Publications at relevant peer-reviewed conferences like RecSys or KDD.

• Knowledge of gaming metrics and KPIs, including player lifetime value (pLTV), retention, and ROAS.

• Familiarity with big data tools like Spark, Dask, or Hadoop, and cloud platforms such as AWS, GCP, or Azure.

• Passion for gaming and a deep understanding of player behavior and game design principles.

If you’re an ML scientist who’s excited about the intersection of gaming and AI, we’d love to hear from you! Send your resume and a brief cover letter outlining your experience and interest in the role to [e-mail].