Senior Data Scientist (Platform Economics & Simulation)

Join PlayStation as a Senior Data Scientist, where you'll play a critical role in shaping how we invest in, retain, and delight our global player base. You'll be responsible for explaining the economics of the platform, building simulation and offline-evaluation tooling, and turning causal understanding into concrete proposals. This role requires a strong background in causal methods, experience in turning causal and economic understanding into decisions, and fluency with large, complex behavioral datasets.

• Expliquer les raisons pour lesquelles la valeur évolue à travers les revenus, la rétention et l'engagement, en utilisant des méthodes de décomposition de la valeur.
• Appliquer le raisonnement causal pour comprendre les modèles et les joueurs, et construire des outils d'évaluation des politiques hors ligne.
• Guider le développement des modèles au sein de l'équipe, en élevant le niveau de réflexion causale et économique.
• Depth in causal methods used to explain and understand systems: treatment-effect estimation, uplift, structural or counterfactual reasoning
• Proven industry experience turning causal and economic understanding into decisions that changed commercial outcomes, in areas such as customer value, retention, pricing, or decisioning
• Fluency with large, complex behavioural datasets and the craft to work with them at scale: Python, SQL, and distributed processing (e.g. PySpark), plus standard ML tooling as the work requires
• Excellent stakeholder communication: you can make a rigorous causal argument land with a non-technical commercial audience and move a decision
• You think in counterfactuals. You instinctively separate incremental effect from what would have happened anyway, and you reason naturally about substitution, cannibalisation, and the economics of a content platform. A background in economics, econometrics, or a similarly causal quantitative discipline is a strong fit
• A strong quantitative academic background, typically a Master's or PhD
• The ability to build, not just analyse: you can implement models, simulation, or offline-evaluation environments and take them to production
• Experience owning ambiguous problems end-to-end: framing the question, choosing the approach, and delivering something the business acts on
• Strong judgement on when a sophisticated approach is warranted versus a simpler one that answers the question
• Reinforcement learning or contextual-bandit decisioning, and offline evaluation for recommendation or decisioning systems
• Background in gaming, e-commerce, or subscription businesses
• Experience with incrementality and uplift modelling, or with experimentation frameworks
• Experience deploying and maintaining business-critical or consumer-facing models
• Experience working in agile, fast-paced environments.