Senior/Staff 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 Senior / Staff Data Scientist, you will help shape how PlayStation measures the impact of products, features and commercial initiatives through world-class experimentation, causal inference and applied data science. Working at the intersection of data science, machine learning, product and commercial strategy, you will develop innovative measurement methodologies, define best practices, and provide technical leadership that enables teams across PlayStation to make faster, more confident business decisions. This role goes beyond traditional A/B testing. You will solve complex measurement problems where controlled experiments are difficult or impossible, applying modern causal inference, statistical modelling and machine learning techniques to generate robust business insights. You will collaborate closely with product, engineering, analytics and business teams to raise the standard of experimentation and evidence-based decision-making across the organisation. This is an opportunity to influence strategic decisions impacting millions of PlayStation players while helping establish best-in-class measurement practices across one of the world's leading entertainment companies. What You'll Be Doing: Develop innovative measurement methodologies across