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Senior Machine Learning Data Scientist

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Come work at the Good Times Factory!

At MAG we have a firm belief that the key to producing great games is teamwork and trust. We trust everyone in the company with the freedom to decide what team they want to work with and how they can most effectively contribute.

In turn, each team owns its respective game and decides on how best to proceed in development. This way, everyone at MAG feels valued and has the opportunity to work on the projects that they love within a positive environment.

In order to drive innovation within the company, we have monthly hackathons during which everyone in the company comes together to learn new things, work on side projects, develop game concepts, and/or build prototypes for new games. We believe that happy people with the freedom to flex their creativity make great entertainment, and this is how we nicknamed ourselves The Good Times Factory. Making great games should be fun, and we encourage that!

The Job:

As a part of the AI team you will play a crucial part of building MAGs implementation of Machine Learning. You will work on a variety of problems such as personalisation, targeting, optimization etc. You will come up with new and interesting hypotheses, test them, and scale them up to massive data sets, so that your algorithms and models can be used to improve critical components for all our games.


  • Leverage your experience to drive best practices in ML and data science projects
  • Develop workflows and processes for data science, in particular machine learning, projects
  • Develop predictive and prescriptive models to personalize our player experience and support our marketing efforts
  • Implement ML models into live games

Required skills:

  • 3+ years of relevant work experience developing, evaluating, deploying and maintaining ML models
  • You have hands-on experience implementing production machine learning systems
  • Experience with Python, Scikit-learn, TensorFlow and Keras
  • You care about agile software processes, data-driven development, reliability, and disciplined experimentation

Or, know someone who would be a perfect fit? Let them know!


Drottninggatan 95A
113 60 Stockholm Directions

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