Data Scientist

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 us create the unknown!

Southeast Asia's largest AAA game development studio with 450 talented team members representing 30+ nationalities. Opening its doors on the sunny shores of Singapore in 2008, Ubisoft Singapore set off on a vision to be a world class video game studio, and in its subsequent years played an essential role in several gaming blockbusters, including just about every Assassin's Creed® game since Assassin's Creed® II, Immortals Fenyx Rising™, and Ghost Recon Online. Its expertise in AAA and live operations, combined with a passion for naval battle gameplay and water technology, pushed the team to lead the development of a brand-new AAA game franchise – Skull and Bones™ which was launched in February 2024.

Job Description

We are looking for a Data Scientist who thrives on creating value, not just building models. This role sits within the Asia Intelligence team, a pragmatic, product-minded group focused on shipping data and AI solutions that make an impact today. You will work closely with engineers, analysts, and stakeholders across Ubisoft to design, build, and evolve AI-powered products that are already in production and growing in ambition.

Success in this role is defined by your ability to deliver alongside your team. We care about shipped outcomes, not just experimentation. If you are energised by moving quickly, doing your work end-to-end, and seeing real players affected by what you build then this is the role for you.

WHAT YOU WILL DO

Your core responsibilities

Design, build, and maintain machine learning models and AI products that are deployed in production and create measurable value for players and the business

Contribute to personalisation and decisioning systems -including recommendation engines, segmentation models, propensity scoring, and Next Best Action frameworks - that directly influence player retention and engagement

Support the development of AI agent architectures and automation workflows that extend the team’s capacity to deliver intelligence at scale

Translate complex stakeholder needs into well-scoped, pragmatic solutions, balancing model sophistication with delivery speed and operational sustainability

Collaborate closely with data analysts, data engineers, and product stakeholders to ensure models are integrated, understood, and acted upon

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

Qualifications

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

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

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

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

Additional Information

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.

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