Lead Data Scientist – Gaming Analytics & ML

Aristocrat Gaming; Barcelona; On-site; EUR 70,000 - 100,000; Full time

Job summary

Product Madness is seeking a Lead Data Scientist to drive statistical analysis, predictive modelling, and machine learning for global players. You will work with game developers, data analysts, and product teams to understand player behavior, tackle business problems, and improve gaming experiences.

You will guide ML initiatives from planning through development, evaluation, and implementation, handling large datasets to build models and analytics tools that support engagement, retention, and

Qualifications

• 3+ years of experience delivering analytics or machine learning projects.
• Strong foundation in statistics, probability, and data analysis.
• Ability to develop, build, and evaluate predictive ML models.
• Experience with A/B testing and experimental design.

Responsibilities

• Coordinate data science projects: define business problems, develop hypotheses, select methods, build solutions, measure results.
• Develop predictive algorithms to support personalisation, engagement, retention, and monetisation.
• Apply statistical methods to answer business questions, including forecasting and causal inference.
• Design and evaluate experiments: plan and analyze A/B tests, interpret results.
• Build analytical tools and reusable models for teams.
• Ensure data quality, validate datasets, and monitor model assumptions.
• Collaborate with Data Engineering, MLOps, and Game Tech teams to productionize solutions.
• Share findings and recommendations with stakeholders.

Skills

Python

SQL

Statistics

Machine learning

A/B testing

Experiment design

Education

Degree in Data Science / Statistics

Tools

GCP

AWS

Azure

Git

Docker

Job description

Product Madness is seeking a Lead Data Scientist to drive statistical analysis, predictive modelling, and machine learning for global players. You will work with game developers, data analysts, and product teams to understand player behavior, tackle business problems, and improve gaming experiences.

You will guide ML initiatives from planning through development, evaluation, and implementation, handling large datasets to build models and analytics tools that support engagement, retention, and