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 Play Station 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 Play Station brand, a name synonymous with entertainment excellence and creativity.

Role Overview

As a Senior / Staff Data Scientist, you will help shape how Play Station 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 Play Station 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 Play Station 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 experimentation, causal inference and advanced analytics that improve the quality, reliability and scalability of business decision-making across Play Station.
• Design robust measurement approaches across randomised experiments, quasi-experimental methods and observational causal inference where controlled experimentation is impractical.
• Research, evaluate and prototype statistical, machine learning and AI techniques to solve complex real-world measurement challenges.
• Apply advanced data science and machine learning techniques where appropriate to complement experimentation and support complex business decisions.
• Define and promote best practices for experiment design, statistical analysis and causal measurement across multiple product and business teams, helping scale experimentation across Play Station.
• Partner closely with senior business leaders, product managers, engineers and analysts to identify high-impact measurement opportunities and ensure product and commercial decisions are supported by rigorous evidence.
• Partner with engineering teams to influence the evolution of Play Station's experimentation platform and measurement capabilities, ensuring statistical best practices are embedded into future platform development.
• Provide technical leadership across multiple product and commercial domains, influencing measurement strategy, analytical standards and long-term technical direction through expertise and collaboration.
• Mentor and develop analysts and data scientists, helping raise technical capability and analytical excellence across the team.
• Champion a culture of evidence-based decision-making by educating stakeholders, sharing best practices, and communicating advances in experimentation, causal inference and applied data science.
• Stay current with emerging developments in statistics, machine learning and AI, identifying opportunities to improve measurement capabilities and analytical workflows.
• Represent the team across Play Station, building strong partnerships, engaging senior stakeholders, and promoting technical excellence in data science and experimentation.

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. Ph D preferred.
• Strong industry experience (5+ years) applying experimentation, causal inference, statistical modelling and measurement science to solve complex business problems.
• Deep expertise in experimental design, A/B testing and modern causal inference methods, including quasi-experimental approaches.
• Experience applying advanced data science, machine learning and statistical modelling techniques to solve complex business problems.
• Expert-level proficiency in Python and SQL for large-scale analytical workflows.
• Experience developing reusable analytical methodologies, frameworks or libraries that improve measurement quality and
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