Data Scientist - Measurement, Experimentation & Causal Inference

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. Role Overview: As a Data Scientist, you will help measure the impact of PlayStation's products, features and commercial initiatives through experimentation, causal inference and applied data science. Working at the intersection of data science, machine learning, product and commercial strategy, you will apply robust analytical techniques to solve complex business problems, generate actionable insights and support evidence-based decision-making across PlayStation. This role goes beyond traditional A/B testing. You will apply modern causal inference, statistical modelling and machine learning techniques to evaluate initiatives where controlled experiments are difficult or impossible, collaborating closely with product, engineering, analytics and business teams to deliver high-quality measurement and insights. This is an opportunity to work on high-impact initiatives affecting millions of PlayStation players while developing your expertise in experimentation, causal inference and applied data science. What You'll Be Doing: Apply measurement methodologies across experimentation, causal inference and advanced analytics to evaluate product and commercial initiatives. Design and execute robust measurement approaches across randomised experiments, quasi-experimental methods and observational causal inference where controlled experimentation is impractical. Apply statistical, machine learning and AI techniques to solve complex measurement challenges and generate actionable business insights. Apply advanced data science and machine learning techniques where appropriate to complement experimentation and support complex business decisions. Contribute to the development and adoption of best practices for experiment design, statistical analysis and causal measurement. Partner closely with product managers, engineers, analysts and business stakeholders to identify high-impact measurement opportunities and ensure product and commercial decisions are supported by rigorous evidence. Collaborate with engineering teams by providing feedback on experimentation and measurement capabilities to improve tooling and workflows. Develop reusable analytical solutions, dashboards and code that improve the quality, consistency and efficiency of measurement. Communicate analytical findings and recommendations clearly to technical and non-technical stakeholders. Stay current with emerging developments in statistics, machine learning and AI, identifying opportunities to improve measurement capabilities and analytical workflows. Contribute to a culture of evidence-based decision-making by sharing knowledge, collaborating across teams and promoting analytical best practices. What We're Looking For: Required: Master's degree (or equivalent industry experience) in Statistics, Economics, Mathematics, Computer Science, Data Science or another quantitative discipline. PhD preferred. 3+ years of industry experience applying experimentation, causal inference, statistical modelling, machine learning or related analytical techniques to solve business problems. Good understanding of experimental design, A/B testing and modern causal inference methods, including quasi-experimental approaches. Experience applying data science, machine learning and statistical modelling t…