Data Scientist | Híbrido in London

Why Sony Interactive Entertainment? Sony Interactive Entertainment isn't just the Best Place to Play — it's also the Best Place to Work. Sony Interactive Entertainment (SIE) is the company behind the PlayStation brand. As a subsidiary of Sony Group Corporation, we're part of a proud legacy of innovation and excellence. SIE is a dynamic technology company, delivering cutting-edge hardware and network services to more than 100 million people and an entertainment leader, home to some of the most beloved and recognizable intellectual properties (IP) in the world. Our role at SIE is to create and nurture the experiences under the PlayStation brand, a name synonymous with entertainment excellence and creativity. At PlayStation, Data Science plays a critical role in shaping how we invest in, retain, and delight our global player base. The CLV team focuses on understanding player behaviour and driving more effective engagement across the player lifecycle — from acquisition and onboarding through to retention, monetisation, and long-term value. As a Data Scientist, you will develop models and insights that help drive more personalised player experiences and inform commercial and product decisions at scale. This role is ideal for an individual who is comfortable owning problems end-to-end — from framing and modelling through to delivering impact — and partnering with stakeholders to support data-informed decision-making. Own the development and delivery of machine learning models for use cases such as churn prediction, purchase propensity, store recommendations, customer lifetime value. Work with large-scale behavioural and transactional data to uncover patterns and opportunities for player growth and engagement. Collaborate within cross-functional teams, including engineering, product, and commercial stakeholders, to ensure solutions are robust, scalable, and aligned with business needs. Partner with stakeholders across commercial, finance, and lifecycle teams to support decision-making with data-driven insights. You bring strong foundations in modelling and data manipulation, and are motivated by applying these to impactful, commercial problems. Experience building predictive models (e.g. churn, propensity, segmentation, or value modelling) in a commercial setting. Proficiency in Python and SQL, and familiarity with common data science and ML libraries. 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. Awareness of modern machine learning approaches (e.g. embeddings, sequence models, deep learning) and interest in applying them to real-world problems. A strong academic background, typically a Master's or Ph.D. in a quantitative or technical field (e.g. Mathematics, Statistics, Computer Science). Familiarity with production environments, MLOps, or data pipelines. Experience working with large-scale data using PySpark or equivalent distributed data processing tools. Experience in gaming, e-commerce, or subscription-based products. Discretionary bonus opportunityPrivate Medical InsuranceDental Scheme25 days holiday per yearOn Site GymSubsidised CaféFree soft drinksOn site barAccess to cycle garage and showersPlease refer to our Candidate Privacy Notice for more information about how we process your personal information, and your data protection rights. Please refer to our Candidate Privacy Notice for more information about what personal information we collect, how we use it, who we share it with, and your data protection rights. All persons will receive consideration for employment without regard to gender (including gender identity, gender expression and gender reassignment), race (including colour, nationality, ethnic or national origin), religion or belief, marital or civil partnership status, disability, age, sexual orientation, pregnancy, maternity or parental status, trade union membership or membership in any other legally protected category. We strive to create an inclusive environment, empower employees and embrace diversity.