Data Scientist (Forecasting)

Join PlayStation as a Data Scientist (Forecasting) and play a critical role in shaping player engagement and value. You will develop machine learning models, work with large-scale data, and collaborate with cross-functional teams to drive measurable improvements in player experiences. This role requires proficiency in Python and SQL, experience with large datasets, and a strong understanding of machine learning techniques.

• Développer des modèles et des insights pour améliorer l'engagement des joueurs et la valeur à long terme.
• Travailler avec des données comportementales et transactionnelles à grande échelle pour identifier des opportunités de croissance.
• Collaborer avec des équipes interfonctionnelles pour garantir que les solutions sont robustes, évolutives et alignées sur les besoins de l'entreprise.
• Proficiency in Python and SQL, and familiarity with common data science and ML libraries
• Experience working with large datasets to generate actionable insights
• You're curious, analytical, and a strong problem-solver, with a structured approach to tackling business problems. You bring strong foundations in modelling and data manipulation, and are motivated by applying these to impactful, commercial problems
• Solid understanding of machine learning techniques (e.g. regression, tree-based models, clustering) and when to apply them, including how to refine and tune them for real-world problems
• Strong communication and collaboration skills, with the ability to clearly articulate insights and work effectively with cross-functional stakeholders
• Ability to independently take a problem from definition through to solution and delivery, demonstrating initiative and ownership
• Experience building predictive models (e.g. churn, propensity, segmentation, or value modelling) in a commercial setting
• A strong academic background, typically a Master’s or Ph.D. in a quantitative or technical field (e.g. Mathematics, Statistics, Computer Science)
• Awareness of modern machine learning approaches (e.g. embeddings, sequence models, deep learning) and interest in applying them to real-world problems
• Experience working with large-scale data using PySpark or equivalent distributed data processing tools
• Familiarity with production environments, MLOps, or data pipelines
• Experience in gaming, e-commerce, or subscription-based products