Define and lead high-impact data science initiatives that influence long-term company strategy and cross-functional priorities. Develop novel algorithms and machine learning models in areas such as personalization efficiency, content valuation, and portfolio optimization. Design, execute, and interpret sophisticated experiments and causal inference studies to measure impact and guide decision-making. Serve as a technical advisor and mentor to data scientists, engineers, and product leaders to drive best practices in experimentation, modeling, and decision science. Partner closely with Engineering, Product, Content, Studio, and Executive teams to embed data into every level of decision-making. Collaborate with Data Engineering and ML Ops to improve data pipelines, feature engineering, and automation across experimentation workflows. Identify emerging methods, tools, and external trends that could reshape how we use data science across the organization.