Senior/Staff Data Scientist - Measurement, Experimentation & Causal Inference
Salary not listed • United Kingdom, London • Full-time
Posted 1mo ago
About the job
Sony Interactive Entertainment is seeking a Senior / Staff Data Scientist to lead the measurement of products, features, and commercial initiatives through advanced experimentation and causal inference. This role involves developing innovative measurement methodologies, defining best practices, and providing technical leadership to enable data-driven decision-making across PlayStation. You will tackle complex measurement challenges beyond traditional A/B testing, applying modern causal inference, statistical modeling, and machine learning techniques to derive robust business insights. Collaboration with product, engineering, analytics, and business teams is key to raising the standard of experimentation and evidence-based decision-making throughout the organization. This is a unique opportunity to influence strategic decisions impacting millions of players and establish best-in-class measurement practices within a leading entertainment company.
Responsibilities
- Develop innovative measurement methodologies in experimentation, causal inference, and advanced analytics to enhance business decision-making quality, reliability, and scalability.
- Design robust measurement approaches using randomized experiments, quasi-experimental methods, and observational causal inference for situations where controlled experimentation is impractical.
- Research, evaluate, and prototype statistical, machine learning, and AI techniques to address complex real-world measurement challenges.
- Apply advanced data science and machine learning techniques 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.
- Partner with senior business leaders, product managers, engineers, and analysts to identify high-impact measurement opportunities.
- Influence the evolution of PlayStation's experimentation platform and measurement capabilities by partnering with engineering teams.
- Provide technical leadership across multiple product and commercial domains, influencing measurement strategy and analytical standards.
- Mentor and develop analysts and data scientists to enhance technical capability and analytical excellence.
- Champion a culture of evidence-based decision-making through education and sharing of best practices.
- Stay current with emerging developments in statistics, machine learning, and AI to improve measurement capabilities.
- Represent the team across PlayStation, building partnerships and promoting technical excellence in data science and experimentation.
Requirements
- Master's degree (or equivalent industry experience) in a quantitative discipline such as Statistics, Economics, Mathematics, Computer Science, or Data Science; PhD preferred.
- 5+ years of industry experience applying experimentation, causal inference, statistical modeling, 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 modeling 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 to improve measurement quality and consistency.
- Demonstrated ability to influence technical direction and drive adoption of best practices through collaboration and leadership.
- Strong stakeholder management, executive communication, and influencing skills.
- Curiosity, creativity, and a pragmatic approach to solving ambiguous, high-impact business problems.
- Familiarity with modern data engineering and analytics tooling (e.g., Databricks, Snowflake, Git, Airflow) is preferred.
- Experience with modern business intelligence and data visualization tools (e.g., Tableau, Domo, Power BI) is preferred.
- Experience applying AI tools, including LLMs, to improve data science workflows is preferred.