Gameloft

We're looking for a Data Scientist to analyze player data, develop machine learning models, and deliver insights that improve game performance and revenue across live titles, including life-simulation and racing games.

🎯 Responsibilities

• Analyze large-scale player data using Python and SQL, turning findings into clear, actionable insights.
• Perform feature engineering on large-scale data from the data warehouse.
• Manage analytical and modeling code with Git.
• Prototype and improve machine learning models and prediction pipelines.
• Apply experimental design, causal inference, and A/B testing to improve performance baselines.
• Move projects from exploratory analysis to deployed models across live game titles.
• Present findings and recommendations to non-technical stakeholders across game teams.
• Collaborate with Data Analysts, Data Engineers, and local game teams across multiple studios worldwide.

🛠️ Requirements

• Experience in game development or the mobile industry.
• Master's degree in a quantitative field, such as computer science, applied mathematics, data science, or a related discipline.
• Proficiency in Python, including pandas, NumPy, scikit-learn, Matplotlib, and seaborn.
• Strong SQL skills for large-scale data analysis.
• Experience with machine learning workflows, including experimental design, causal inference, and A/B testing.
• Experience with Git and large-scale data in a data warehouse environment.
• Ability to communicate and present analytical work in English to non-technical stakeholders.
• Ability to translate complex analysis into clear, actionable recommendations.

📈 What success looks like

• During your first months, you will become familiar with the data infrastructure and deliver your first exploratory analyses.
• By the middle of your onboarding, you will own features or models end to end, frame problems clearly, and present your work to non-technical stakeholders.
• By the end of your onboarding, you will conduct experiments independently and deliver improvements adopted across game teams.

🤝 Collaboration

• Report to the Lead Data Scientist within the Global Data Science and Analytics team.
• Work closely with Data Analysts, Data Engineers, and game teams.
• Collaborate with colleagues across multiple studios and diverse professional backgrounds.

🚀 Career development

• Progress toward more senior roles by leading increasingly large and complex projects.
• Shape game performance and business results through data-driven insights.

🧭 Recruitment process

• Recruitment screen: Discuss your background, role alignment, and questions.
• Case study: Complete a practical data science test.
• First interview: Present your test and discuss your approach, reasoning, and methodologies in greater depth.
• Final interview: Discuss your experience, vision, and approach to data topics at a broader level. This stage is optional.

🤗 Benefits

• Permanent, full-time contract with comprehensive social benefits.
• 25 vacation days per year plus one day off for your birthday.
• Private medical insurance.
• Flexible compensation through a Ticket Restaurant card.
• Free language courses.
• Merit-based salary progression system.
• Competitive initial salary package.