Senior Data Scientist

Overview In this Senior Data Scientist role, you will shape how data informs Play Station investments and strategy by modeling player value and long-term impact. You will partner with Finance, Strategy and Platform to translate insights into scalable decisions that drive growth. You’ll own problem definitions, apply advanced techniques, and communicate results to both technical and non-technical audiences. This is a values-driven opportunity to influence portfolio decisions at scale within a leading entertainment tech company. Compensation / Benefitsmedical, dental, visionmatching 401(k)paid time offwellness programemployee discounts for Sony productsbonus eligibility Responsibilities Design and deliver advanced modelling to quantify player value, incremental impact, and long-term platform value using causal inference, forecasting, optimization and ML as appropriate Measure incremental effects of launches, investments, and external events and translate findings into actionable value attribution Build optimization and scenario models to inform long-range planning under real-world constraints Own ambiguous problem spaces and translate them into tractable, measurable solutions Partner with cross-functional teams to ensure robustness, trust, and adoption of value-driving products Evaluate and select modelling approaches balancing rigour, performance, scalability, interpretability, and business impact Mentor other data scientists and contribute to best practices across the team Communicate complex modelling approaches and outcomes clearly to both technical and non-technical audiences, including Finance leadership Key requirements Proven experience delivering analytical and modelling solutions in customer value, incrementality, forecasting, or investment decisioning Experience with optimization or operations research or strong quantitative foundation to pick these up quickly Strong grounding in causal inference and impact measurement; ability to assess assumptions and scope approaches accordingly Experience owning projects end-to-end from problem definition to delivery and adoption Ability to work with large, complex datasets and translate into scalable solutions Excellent stakeholder management and communication skills with finance and business partners Proficiency in Python and SQL; comfort with PySpark or distributed data processing tools Master's or PhD in operations research, machine learning, statistics, economics, or related field Stakeholder management Communication and storytelling with non-technical audiences Proactive problem-solving and collaboration PythonSQLPySpark