Data Scientist

Requirements

• Product- and business-oriented, with the ability to connect data work to real game impact
• Comfortable working and presenting with non-technical stakeholders, with strong ability to simplify and communicate complex topics at a high level
• Able to translate analytical insights into clear, actionable recommendations

Benefits

Additional Information

WHAT YOU WILL BE WORKING ON Main challenge As a Data Scientist, you'll dive into massive streams of player data from globally played games, turning behaviors into insights and machine learning models that directly shape how millions of players experience our games and how our titles perform worldwide. What it means on a daily basis You will work on different projects across various game genres, including life simulation and racing games. Analyze large-scale player data in a fast-paced gaming environment and transform it into clear, actionable insights Perform advanced feature engineering using large-scale data from our data warehouse Prototype machine learning models to improve existing performance baselines Contribute to the development of internal tracking, prediction pipelines, and monitoring systems Improve experimental capabilities through robust experimental design and statistical methods, including causal inference and A/B testing What success will look like You are able to take ownership of a project end-to-end, from clearly framing and presenting the problem to non-technical stakeholders to delivering actionable insights and recommendations independently. Who you would be working with As a Data Scientist in our Global Data Science and Analytics team, you will be reporting to our Lead Data Scientist and collaborate very closely with other data scientists, data analysts and data engineers in the team. Your recruitment journey First interview (TA): An initial discussion to explore how the role aligns with your background and to address your main questions. Test : You will be given a case study to complete. Second interview (Hiring Manager): A technical interview focused on presenting your test and discussing your approach, reasoning, and methodologies in more depth. Final interview (VP Data): A conversation to discuss your experience, vision, and how you approach data topics at a broader level. Where this role can take you Grow into a more senior position while taking ownership of increasingly large and complex projects with greater impact on game performance and business outcomes. WHAT YOU NEED TO SUCCEED A first full-time professional experience (CDD/CDI) in tech, gaming, or a similar industry is preferred, as the role requires autonomy and the ability to manage day-to-day responsibilities independently Proficiency in Python (especially pandas, numpy, scikit-learn, matplotlib, seaborn, etc.) Strong SQL skills Experience with Git and machine learning workflows, including experimental design and key statistical methods Ability to work with large-scale data

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Company Intel

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