About the role
Job Overview
Gameloft Barcelona is seeking a Data Scientist to join the Gameloft Global Data team. The role focuses on deep diving into massive streams of in-game player data, prototyping, and deploying machine learning models to increase game revenue. You will move projects from exploratory analysis to deployed models across live titles, including life-simulation and racing games.
Day-to-Day Responsibilities
- Analyze large-scale player data using Python and SQL to transform it into clear, actionable insights.
- Perform feature engineering on large-scale data from the data warehouse, managing code with Git.
- Prototype and improve machine learning models and prediction pipelines, utilizing experimental design, causal inference, and A/B testing to raise performance baselines.
- Present findings and recommendations to non-technical stakeholders across the game teams.
Onboarding & Success Metrics
- First months: Ramp up on data infrastructure and deliver initial exploratory analyses.
- Middle of onboarding: Responsibility for features or models end-to-end, framing problems clearly and presenting them to non-technical stakeholders.
- End of onboarding: Conducting experiments and delivering improvements independently, with insights adopted across game teams.
Team & Collaboration
- Reporting to the Lead Data Scientist.
- Collaborate closely with Data Analyst and Data Engineering teams.
- Work with local game teams across multiple studios worldwide, including Paris, Barcelona, Montreal, Sofia, and Bucharest.
Recruitment Process
- First interview: Initial discussion regarding background and questions.
- Test: Completion of a case study.
- Second interview: Technical interview focusing on the test, methodology, reasoning, and approach.
- Final interview: Discussion regarding experience, vision, and high-level data strategy.
Career Progression
This role serves as a stepping stone toward senior positions, with opportunities to lead increasingly complex projects that impact game performance and business results.
Qualifications
- Education: Master's degree in a quantitative field (computer science, applied mathematics, data science, or related).
- Technical Skills:
- Proficient in Python (pandas, NumPy, scikit-learn, Matplotlib, seaborn).
- Proficient in SQL for large-scale data analysis.
- Skilled in machine learning workflows, including experimental design, causal inference, and A/B testing.
- Experienced with Git.
- Comfortable working with large-scale data in a data warehouse environment.
- Soft Skills:
- Ability to communicate and present to non-technical stakeholders in English, translating analytical work into clear, actionable recommendations.
Benefits & Compensation
- Permanent, full-time contract 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.
Work Environment
- Barcelona studio provides career development opportunities and a positive, centrally located working environment.
- Focus on supportive working conditions, a balanced work-life approach, and a collaborative team mindset.