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

Sony Interactive Entertainment
United Kingdom, London
Workplace: HybridFull timeFunction: Data Science & Machine LearningExperience: 5+ yearsEducation: mastersSkills: ["Stakeholder management","Executive communication","Influencing","Mentoring","Problem-solving"]

Shape how PlayStation measures product and commercial impact by building experimentation and causal inference approaches beyond traditional A/B testing. Develop scalable measurement methodologies, prototype statistical/ML/AI techniques, and define best practices for experiment design, analysis, and evidence-based decision-making. Partner with product, engineering, analytics, and business leaders to translate rigorous causal evidence into faster, more confident decisions at global scale.

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Sony Interactive Entertainment
Sony Interactive Entertainment
10 hours ago

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

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Source: Company careers pageValidated by: Fursa AI
Last checked: 9 hours agoStatus: Live
Reposted: similar role first listed 1 month ago

Job Summary

Shape how PlayStation measures product and commercial impact by building experimentation and causal inference approaches beyond traditional A/B testing. Develop scalable measurement methodologies, prototype statistical/ML/AI techniques, and define best practices for experiment design, analysis, and evidence-based decision-making. Partner with product, engineering, analytics, and business leaders to translate rigorous causal evidence into faster, more confident decisions at global scale.
Location: United Kingdom, London
Workplace: Hybrid
Employment Type: Full time
Job Function: Data Science & Machine Learning
Seniority: Mid level

Key Responsibilities

  • •Develop and scale measurement methodologies across experimentation, causal inference, and advanced analytics to improve decision quality and reliability.
  • •Design measurement approaches across randomized experiments, quasi-experiments, and observational causal inference when controlled testing is impractical.
  • •Research, evaluate, and prototype statistical, machine learning, and AI techniques for complex real-world measurement challenges.
  • •Define and promote best practices for experiment design, statistical analysis, and causal measurement across product and business teams.
  • •Provide technical leadership, mentor analysts and data scientists, and partner with senior leaders to drive evidence-based decision-making.

Pay and Benefits

Perks:Health InsuranceDentalHybrid WorkingAnnual LeaveGym Membership

Key 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 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 using advanced data science, machine learning, and statistical modelling techniques for complex business decisions.
  • •Expert-level proficiency in Python and SQL for large-scale analytical workflows.
Experience:5+ years
Education:Master's in Statistics, Economics, Mathematics, Computer Science, Data Science (or another quantitative discipline)
Skills:Stakeholder managementExecutive communicationInfluencingMentoringProblem-solving
Languages:English
Tech Stack:PythonSQLDatabricksSnowflakeGitAirflowTableauDomoPower BILarge language models (LLMs)Machine learningAI

Company Brief

Sony Interactive Entertainment
Develops and publishes PlayStation hardware, software, and digital services, operating the PlayStation platform and ecosystem for gaming, entertainment, and network services worldwide.
Industry: Gaming
Company Size: Enterprise (1,001+ employees)
Revenue: USD 1B+
Growth: Established Company
Headquarters: San Mateo, United States
Founded: 1993
WebsiteLinkedIn