Additionalinformation

Additional Information

WHAT’S IN IT FOR YOU

Benefits

• Permanent contract, full-time employment with comprehensive Social Benefits.
• 25 vacation days per year + Birthday day off.
• Private medical health insurance.
• Flexible compensation with Ticket Restaurant Card.
• Free language courses.
• Work-from-home hybrid model.
• Merit based salary progression system and a competitive initial salary package.

Life at Gameloft

Our Barcelona studio offers real career development opportunities and a positive working environment in a centrally located office. We value supportive working conditions and a balanced work-life approach, and our teams work together with a collaborative mindset.

Ready to level up your career? Apply now with your CV in English.

Companydescription

Company Description

Jobdescription

Job Description

WHAT YOU WILL BE WORKING ON

Gameloft Barcelona is seeking a Data Scientist to join Gameloft Global Data team.

As a Data Scientist, you will be able to deep dive into our massive streams of player data in-game, prototype and deploy machine learning models to increase game revenue. You will help move projects from exploratory analysis to deployed models across live titles, including life-simulation and racing games.

What it means on a daily basis

• 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.

What success will look like

In your first months, you will ramp up on our data infrastructure and deliver your first exploratory analyses.By the middle of your onboarding, you will be responsible for features or models end-to-end, framing problems clearly and presenting them to non-technical stakeholders. By the end of your onboarding, you will be conducting experiments and delivering improvements on your own, with your insights adopted across the game teams.

Who you will be working with

As a Data Scientist in our Global Data Science and Analytics team, you will be reporting to our Lead Data Scientist and collaborate very closely with other Data teams (Data Analyst, Data Engineering) and with our local Game teams. Our teams operate across multiple studios worldwide, including Paris, Barcelona, Montreal, Sofia, Bucharest, and others, offering opportunities to collaborate with colleagues from diverse backgrounds and perspectives.

Your recruitment journey

• Recruitment screen: An initial discussion to explore how the role aligns with your background and to address your main questions.
• Test: You will be given a case study to complete.
• First Interview: A technical interview focused on presenting your test and discussing your approach, reasoning, and methodologies in more depth.
• Final interview (optional): A conversation to discuss your experience, vision, and how you approach data topics at a broader level.

Where this role can take you

This role can be a stepping stone toward a more senior position, with the possibility of leading increasingly large and complex projects, so that your work shapes game performance and business results more widely over time.

Qualifications

WHAT YOU NEED TO SUCCEED

• 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.

WHO YOU ARE

• Able to communicate and present to non-technical stakeholders in English, translating analytical work into clear, actionable recommendations.