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Rockstar Games

Data Scientist, Live Ops

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Rockstar Games
🇺🇸 Carlsbad, CA

At Rockstar Games, we create world-class entertainment experiences.

A career at Rockstar Games is about being part of a team working on some of the most creatively rewarding and ambitious projects to be found in any entertainment medium. You would be welcomed to a dedicated and inclusive environment where you can learn, and collaborate with some of the most talented people in the industry.

Rockstar Games is on the lookout for talented Data Scientists who possess a passion for both games, and big data. This is a full-time permanent position based out of Rockstar’s unique game development studio in Carlsbad, CA.


  • The Rockstar Analytics team provide insights and actionable results to a wide variety of stakeholders across the organization in support of their decision making.
  • We collaborate as a global team to develop cutting-edge data pipelines, data products, data models, reports, analyses, and machine learning applications.
  • The Game Analytics vertical is heavily focused on understanding our players and using data to improve our games.


  • Assure Rockstar’s ongoing competitive advantage through best-in-class Machine Learning initiatives that have a high potential of applicability in industry.
  • Identify and contribute to analytic experiments aligned with long-term strategic initiatives.
  • Develop and contribute to machine learning enabled solutions to address critical game analytics questions.
  • Build models enabling business stakeholders to evaluate scenarios.
  • Design, build, and participate in validation tests to assess the efficiency of the model (or algorithm) in place and provide strategic insights to stakeholders who directly work on our games.
  • Conduct proactive in-depth analysis and predictive modeling to uncover hidden opportunities.
  • Partner with data analysts, data engineers, data scientists, and stakeholders to better understand requirements, find bottlenecks, and implement resolutions.
  • Collaborate with the Analytics Tech lead to establish best practices for repeated application.
  • Work within a team of data analysts and engineers.


  • 2+ years in data science or similar role in the video game industry.
  • 2+ years of experience in machine learning / statistical languages and systems such as Python, R.
  • Bachelor’s degree in Computer Science or related field, with a strong quantitative background.
  • Passion for Rockstar Games and our titles.


  • Knowledge of machine learning techniques such as k-NN, Naive Bayes, SVM, Decision Forests, Data Mining, Clustering, and Classification.
  • Experience in pushing models to production and iterating on models in production.
  • Proficiency in statistics such as distributions, predictive modeling, data validation, statistical testing, and regression.
  • Ability to develop and maintain good relations and communicate with people at all hierarchical levels.
  • Strong problem-solving skills.
  • Ability to reconcile technical and business perspectives.
  • Autonomy and entrepreneurship.
  • Strong team spirit.


Please note that these are desirable skills and are not required to apply for the position.

  • 2+ years using SQL (or a SQL-like language) required, other programming experience highly preferred.
  • Experience with Hadoop and PySpark.
  • Experience with Azure ML.
  • Graduate degree (MBA, MSc or Master’s, PHD), an asset.
  • Game industry experience strongly desired.


Please apply with a resume and cover-letter demonstrating how you meet the skills above. If we would like to move forward with your application, a Rockstar recruiter will reach out to you to explain next steps and guide you through the process.

Rockstar is proud to be an equal opportunity employer, and we are committed to hiring, promoting, and compensating employees based on their qualifications and demonstrated ability to perform job responsibilities.

If you’ve got the right skills for the job, we want to hear from you. We encourage applications from all suitable candidates regardless of age, disability, gender identity, sexual orientation, religion, belief, or race.