Data Scientist

In six months:

• You will have developed a strong working knowledge of our data infrastructure, player behaviour data, and live operations context across active titles
• You will have familiarised yourself with our suite of ML models spanning forecasting, propensity modelling, and player decisioning, and made meaningful contributions to at least one
• You will have expanded our AI/ML programme to cover additional player engagement scenarios and franchises, including personalisation and player decisioning capabilities
• You will have built trusted working relationships with key stakeholders, understanding their needs and how data science can serve them

In twelve months:

• You will be a core contributor to the evolution of our personalisation and player engagement capabilities, including our Next Best Action engine and propensity modelling programme
• You will have helped shape the roadmap for new AI product opportunities, drawing on a clear view of where ML and agent-based approaches can generate near-term value for the business

Essential:

• At least 3 years’ experience in an applied Data Science or ML role, with a track record of shipping models or AI products into production
• Demonstrated ability to deliver measurable outcomes through applied ML: your work has made it into the hands of end users, not just into a notebook
• Strong collaborative instincts: you understand that impact comes from working well with others, not from working alone
• Pragmatic problem-solver who can scope work appropriately, move fast where needed, and know when good enough beats perfect
• Comfortable working across disciplines, from game designers and producers to analysts and engineers, with strong communication skills to match

Desired:

• Hands-on experience building personalisation engines, recommendation systems, or player decisioning frameworks
• Work experience with marketing decisioning platforms such as Adobe Marketing Cloud, Salesforce, Pega, Braze, or similar
• Experience designing or contributing to AI agent architectures and agentic workflows
• An interest in games, entertainment, or consumer-facing digital products where player or user behaviour is central to the work

TECHNICAL REQUIREMENTS

Essential:

• Strong Python skills, including experience writing production-grade code beyond notebook prototypes
• Solid SQL skills for data exploration, feature engineering, and pipeline work
• Hands-on experience with ML frameworks such as scikit-learn, LightGBM, PyTorch, or Spark ML
• Expert-level proficiency in Databricks and/or Snowflake, with experience deploying and managing models in a cloud data platform environment
• Version control proficiency (git) and familiarity with collaborative development workflows

Desired:

• Experience with MLflow, Delta Lake, or similar tools for model tracking and data management in Databricks environments
• Familiarity with Snowflake Cortex or Databricks Genie for AI-assisted analytics
• Experience building or integrating LLM-based agents or tool-use frameworks
• Familiarity with API development and the deployment of model-serving endpoints

We are working to enrich players’ lives through unique and memorable gaming experiences and by improving the positive impacts of our games. To get there, we are creating a safer, more inclusive work environment, we are giving back to the communities where Ubisoft operates by working with local non-profit partners and by working to reduce the environmental impact of our business. We are an equal-opportunity employer and value diversity at our company. We do not discriminate on the basis of race, ethnicity, religion, gender, sexual orientation, age or disability status.

Come on board and experience #LifeAtUbi for yourself, we are always on the lookout for talents who thrive in bringing their A-game to work. If this sounds like you, shoot us your resume, portfolio, and anything else to show that you’re serious about fun!