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, translate business problems into actionable strategies, and collaborate with cross-functional teams. This role requires a strong understanding of machine learning techniques, proficiency in Python and SQL, and experience building predictive models in a commercial setting.

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

Responsibilities

• Développer des modèles et des insights pour améliorer l'engagement des joueurs et la valeur à long terme.
• Travailler en collaboration avec des équipes interfonctionnelles pour traduire le comportement des joueurs en stratégies exploitables.
• Posséder le développement et la livraison de modèles d'apprentissage automatique pour des cas d'utilisation tels que la prédiction de l'attrition.

Requirements

• 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
• Awareness of modern machine learning approaches (e.g. embeddings, sequence models, deep learning) and interest in applying them to real-world problems
• Proficiency in Python and SQL, and familiarity with common data science and ML libraries
• Experience building predictive models (e.g. churn, propensity, segmentation, or value modelling) in a commercial setting
• Ability to independently take a problem from definition through to solution and delivery, demonstrating initiative and ownership
• A strong academic background, typically a Master’s or Ph.D. in a quantitative or technical field (e.g. Mathematics, Statistics, Computer Science)
• Strong communication and collaboration skills, with the ability to clearly articulate insights and work effectively with cross-functional stakeholders
• Experience working with large datasets to generate actionable insights
• Familiarity with production environments, MLOps, or data pipelines
• Experience working with large-scale data using PySpark or equivalent distributed data processing tools

Preferred

• Experience in gaming, e-commerce, or subscription-based products