Data Scientist

November 6, 2026

Hybrid

Senior

Barcelona, Spain

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English is required
English CV required

Description

Gameloft Barcelona is hiring a Data Scientist for its Global Data team to work with massive streams of in-game player data. The role involves prototyping and deploying machine learning models to increase game revenue across live titles, including life-simulation and racing games. You will move projects from exploratory analysis to deployed models and present insights to non-technical stakeholders across international studios

Responsibilities

Analyse large-scale player data with Python and SQL, transforming it into clear, actionable insights
Perform feature engineering on large-scale data from the data warehouse, managing your code with Git
Prototype and improve machine learning models and prediction pipelines, using experimental design, causal inference, and A/B testing to raise performance baselines
Present findings and recommendations to non-technical stakeholders across the game teams
Ramp up on the data infrastructure and deliver your first exploratory analyses in your first months
Become responsible for features or models end-to-end, framing problems clearly and presenting them to non-technical stakeholders
Conduct experiments and deliver improvements on your own, with your insights adopted across the game teams
Collaborate closely with Data Analyst and Data Engineering teams and local game teams across multiple studios

Requirements

Experience in game development or the mobile industry
Master's degree in a quantitative field (computer science, applied mathematics, data science, or related)
Proficient in Python (pandas, NumPy, scikit-learn, Matplotlib, seaborn) and in SQL for large-scale data analysis
Skilled in machine learning workflows, including experimental design, causal inference, and A/B testing
Experienced with Git and comfortable working with large-scale data in a data warehouse environment
Able to communicate and present to non-technical stakeholders in English, translating analytical work into clear, actionable recommendations