Senior/Staff Data Scientist - Measurement, Experimentation & Causal Inference

In this role you will shape how PlayStation measures product and commercial impact through advanced experimentation, causal inference, and applied data science. You will lead methodological development and set best practices, enabling cross-functional teams to make faster, evidence-based decisions. You’ll tackle complex measurement problems beyond traditional A/B tests, driving robust insights at scale. This position offers influence over strategic decisions impacting millions of players and the opportunity to advance PlayStation’s measurement platform and analytics capabilities.

• Discretionary bonus opportunity
• Hybrid Working (FlexModes)
• Private Medical Insurance
• 25 days annual leave
• On-site gym
• Subsidised café

• Develop innovative measurement methodologies across experimentation, causal inference, and advanced analytics to improve decision quality
• Design robust measurement approaches for randomized, quasi-experimental, and observational methods
• Research and prototype statistical, ML, and AI techniques for real-world measurement challenges
• Apply advanced data science to complement experimentation in business decisions
• Define and promote best practices for experiment design and analysis across product/ business teams
• Partner with senior leaders, product managers, engineers, and analysts to identify high-impact opportunities
• Collaborate with engineering to evolve PlayStation's experimentation platform and embed statistical best practices
• Provide technical leadership across product and commercial domains and guide long-term direction
• Mentor and develop analysts and data scientists to raise technical capability
• Champion evidence-based decision-making and stay current with advances in statistics, ML, and AI
• Represent the team to stakeholders and promote technical excellence in data science and experimentation

• Master’s degree (or equivalent) in a quantitative discipline; PhD preferred
• 5+ years of industry experience applying experimentation, causal inference, and measurement science
• Deep expertise in experimental design, A/B testing, and quasi-experimental methods
• Experience applying DS/ML techniques to solve complex business problems
• Expert Python and SQL for large-scale analytical workflows
• Experience developing reusable analytical methodologies or libraries
• Ability to influence technical direction and drive adoption through collaboration and stakeholder engagement
• Strong stakeholder management and executive communication skills
• Curiosity, creativity, and pragmatic problem-solving in ambiguous, high-impact contexts

• Stakeholder management
• Executive communication
• Collaborative mindset
• Experimental design
• A/B testing
• Causal inference (quasi-experimental methods)