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Data Scientist - Generative AI

  • Montreal, QC, Canada

Full-time

This opening has closed.

The original listing is kept below for reference.

Job details

Job type
Full-time
Closing date
Posting language
English
Posted

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Original job description

Archived listing. The details below describe a past opening.

Job Description

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!

Qualifications

Job Description

As a data scientist at Ubisoft Montréal, you will contribute to a technology product that brings generative artificial intelligence (AI) into game features. You’ll work with colleagues in data, programming, game and narrative design, and animation. Together, you’ll explore how generative AI can create engaging gameplay experiences and test those experiences with players. The team’s work also spans research and development, product development, short game projects, and collaboration across studios.

What You’ll Do


  • Define goals and evaluation methods using design team requirements and player data
  • Build prototypes and train machine learning models to meet those goals
  • Work with machine learning engineers to hand over prototypes and set measures of success for integration
  • Review AI behavior with designers and find ways to improve gameplay
  • Identify opportunities for experimentation and innovation
  • Explain your work and results clearly to a range of audiences


Additional Information

What you bring to the team


  • Bring data science experience from projects involving interactive products, such as games, applications, or real-time systems
  • Use Python and TensorFlow or PyTorch
  • Apply statistics and evaluation methods, including exploratory data review, statistical tests, and comparisons between two versions
  • Review complex, sequential data from interactive systems
  • Draw on your knowledge of large language models
  • Turn client needs into specifications through careful listening and understanding, while organizing your work and bringing an interest in video games
  • Communicate in English, in writing and conversation, with contacts in different countries as part of the role’s international collaboration


Experience with PySpark is an asset.

What To Send Our Way


  • Send your CV highlighting relevant skills and experience
  • Share links to relevant data science or machine learning projects
More about this job

Responsibilities

Define goals and evaluation methods, analyze player and interactive-system data, and build prototypes and machine learning models for generative AI game features. Collaborate with engineers and game teams to evaluate AI behavior, improve gameplay, support integration, and identify opportunities for experimentation.

Requirements

Candidates should have data science experience with interactive products and be able to use Python and TensorFlow or PyTorch, apply statistical evaluation methods, and analyze complex sequential data. Knowledge of large language models, clear communication, and the ability to translate client needs into specifications are expected; PySpark experience is an asset.

Skills

  • Data Science
  • Python
  • TensorFlow
  • PyTorch
  • Machine Learning
  • Generative AI
  • Large Language Models
  • Statistical Analysis
  • Exploratory Data Analysis
  • Sequential Data Analysis
  • Model Evaluation
  • Prototyping
  • Player Data Analysis
  • Cross-Functional Collaboration
  • Communication
  • PySpark

Visa sponsorship

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Categories

  • Data & Analytics
  • Technology
  • Science & Research
  • Software
  • Creative & Media

Keywords

  • Data Science
  • Generative AI
  • Machine Learning
  • Python
  • TensorFlow
  • PyTorch
  • PySpark
  • Large Language Models
  • Interactive Products
  • Video Games
  • Game Features
  • Player Data
  • Prototyping
  • Model Training
  • Exploratory Data Analysis
  • Statistical Tests
  • Version Comparisons
  • Sequential Data
  • Model Evaluation
  • AI Behavior
  • Gameplay
  • Research And Development
  • Product Development
  • Experimentation
  • Cross-Functional Collaboration
  • Game Design
  • Narrative Design
  • Animation

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