RemoteFull timeMid levelPosted today
Apply with JobAssistAbout the role
- 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
- 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 You’ll Influence:
- Measurement for PlayStation’s product and commercial initiatives
- High-quality experimentation and causal inference across product and business teams
- Product and commercial decisions through rigorous analytical evidence
- The continued evolution of PlayStation’s measurement and experimentation capabilities- Strong stakeholder management and communication skills, with the ability to explain technical concepts clearly to both technical and non-technical audiences
- Master’s degree (or equivalent industry experience) in Statistics, Economics, Mathematics, Computer Science, Data Science or another quantitative discipline. PhD preferred
- Strong proficiency in Python and SQL for analytical workflows
- 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 techniques to analyse complex datasets and generate actionable insights
- 3+ years of industry experience applying experimentation, causal inference, statistical modelling, machine learning or related analytical techniques to solve business problems
- A collaborative mindset with a passion for continuous learning and improving analytical capabilities
- Experience developing robust analytical solutions using sound statistical principles and software engineering best practices
- Curiosity, creativity and a pragmatic approach to solving ambiguous business problems
- Experience working in gaming, digital products, consumer technology, e-commerce or subscription businesses
- Familiarity with modern data engineering and analytics tooling such as Databricks, Snowflake, Git and Airflow
- Experience with modern business intelligence and data visualisation tools such as Tableau, Domo or Power BI
- Experience applying AI tools, including large language models (LLMs), to improve data science workflows and analytical productivity
- Experience developing reusable analytical frameworks, libraries or internal tooling
- Experience presenting analytical findings and recommendations to cross-functional stakeholders
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