Ubisoft is a global leader in gaming with teams across the world creating original and memorable gaming experiences, from Assassin’s Creed, Rainbow Six to Just Dance and more. We believe diverse perspectives help both players and teams thrive. If you’re passionate about innovation and pushing entertainment boundaries, join our journey and help create the unknown!
As a Data Scientist at Ubisoft Paris, you will help transform player and audience data into actionable insights that support business and marketing decisions across Ubisoft’s game portfolio. You will work closely with international stakeholders to develop machine learning models, deliver audience analytics, and support data-driven initiatives throughout the lifecycle of our games.
What you’ll do
- Develop data science initiatives that support business goals and improve audience understanding
- Build and deploy machine learning models to predict player behaviors, including churn, engagement, and audience segmentation
- Design and evaluate advanced analytical approaches such as scoring, attribution, and behavioral modeling
- Analyze player and customer data to generate clear and actionable insights
- Create and maintain datasets, dashboards, and analytical tools using data science and analytics platforms
- Partner with marketing and business teams to understand objectives and translate needs into analytical projects
- Recommend methodologies and data solutions adapted to business use cases
- Present findings and support stakeholders in applying data-driven recommendations
- Contribute to the continuous improvement of team methodologies and best practices
- Collaborate with cross-functional teams including Marketing, CRM, Finance, Media, and Research
What you bring to the team
- Experience working with Python and SQL
- Knowledge of machine learning, statistical modeling, and AI methodologies
- Experience developing and deploying analytical or predictive models
- Familiarity with Databricks and lakehouse data environments
- Understanding of generative AI and large language model applications
- Strong data interpretation and problem-solving skills
- Collaborative communication and presentation skills
- Ability to translate complex data into practical business recommendations
