Data Scientist - Asia Intelligence

About the role

Ubisoft Singapore, part of Ubisoft's Asia Intelligence team, is looking for a Data Scientist who creates value by shipping models and AI products rather than just experimenting. The team works with engineers, analysts and stakeholders to design and evolve AI-powered products that are already in production and growing in ambition. Success is measured by shipped outcomes and the impact on players.

Key responsibilities

• Design, build and maintain machine learning models and AI products deployed in production, delivering measurable value for players and the business
• Contribute to personalisation and decisioning systems such as recommendation engines, segmentation models, propensity scoring and Next Best Action frameworks that affect player retention and engagement
• Support AI agent architectures and automation workflows that extend the team's capacity to deliver intelligence at scale
• Turn stakeholder needs into pragmatic solutions that balance model sophistication with delivery speed and operational sustainability
• Work with data analysts, data engineers and product stakeholders so models are integrated, understood and acted upon

Required profile

• 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 used by end users, not just notebooks
• Strong collaboration skills and comfort working across disciplines, from game designers to engineers
• Desired: hands-on experience with personalisation engines, recommendation systems or player decisioning frameworks, and experience with marketing decisioning platforms such as Adobe Marketing Cloud, Salesforce, Pega or Braze

Required skills

• Strong Python, including production-grade code beyond notebooks
• Solid SQL for data exploration, feature engineering and pipelines
• ML frameworks such as scikit-learn, LightGBM, PyTorch or Spark ML
• Expert-level Databricks and/or Snowflake, with deployed models in a cloud data platform
• Git and collaborative development workflows
• Desired: MLflow, Delta Lake, Snowflake Cortex or Databricks Genie, LLM-based agents, API development and model-serving endpoints