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The Data Intelligence and Analytics (DnA) team sits at the center of the Disney Entertainment Direct-to-Consumer (DTC) business, powering decisions across our streaming portfolio with data science, analytics, and decision frameworks. As Vice President, Content Analytics, you will lead a team composed primarily of data scientists, alongside analytics talent, that builds the data science products, tools, and forecasts supporting DTC Content Strategy across Disney+ and Hulu, with influence that extends to content decisions shaping Disney Entertainment more broadly, particularly TV. 

This is a senior leadership role for an executive who is equal parts strategist, detective, scientist, and builder. You will be the trusted and objective data science and analytics partner to DTC Content Planning & Partnerships, International Content, Strategic Programming, and Emerging Media, Finance, and Disney Entertainment TV and Studios. You will lead the development of predictive models, forecasting systems, and decision tools, and help translate complex audience, engagement, and financial signals into clear, defensible perspectives and recommendations to guide decisions on content valuation, portfolio composition, global investment, and the balance between originals, licensing, and partnership strategies. You will also serve as the data science and analytics anchor across cross-functional squads driving Engagement, Retention, and AI initiatives, and will partner closely with the rest of DnA to ensure content data science and analytics are integrated, consistent, and accelerating outcomes across the business. 

Responsibilities 

• Define and lead the data science and analytics vision and multi-year roadmap for Content Analytics, elevating the function into a decision-grade capability that informs content valuation, licensing, global content investment, and portfolio strategy. 

• Build and lead high-performing teams of data scientists and analysts across Engagement Analytics, Content Analytics, and Strategic Forecasting & Decision Science, including leaders responsible for advanced models and tools for forecasting, survival and segmentation, and frameworks for decision making, insights, and optimization, as well as analytics for content strategy, programming, and title-level analysis. 

• Lead the development and implementation of predictive machine learning models, time series forecasting, survival and segmentation models, and causal inference methods that support content investment, engagement, incrementality, and retention decisions. Continuously improve existing models and architect and prototype new ones, partnering with engineering to operationalize models into production. 

• Architect and execute a multi-year data science and analytics roadmap for content, including the evolution of operating models, methodologies, models, tools, technology, and data products that enable both deep expert analysis and scaled self-serve usage. 

• Be an instrumental leader in the planning and evolution of methodological innovation, serving as a future-focused voice on data science, AI, and analytics internally and with partners. 

• Approach model and product development from a client-focused process, including needs assessment, requirements gathering, prototyping, validation, and partner engagement, ensuring solutions are adopted and drive decisions. 

• Serve as a data science and analytics thought partner to senior leadership in DTC Content Planning & Partnerships, Subscriber Planning, and Finance, leading development of advanced forecasting and scenario planning models in coordination with the broader DnA Data Science function. 

• Build and operationalize clear, consistent frameworks, methodologies, models, and tools that support title-level decisions, content valuation, portfolio composition and prioritization, global optimization, audience behavior, and originals vs. licensing vs. partnership trade-offs. 

• Proactively identify opportunities where data science modeling and AI applications can benefit content strategy and planning; roadmap, execute, and implement for measurable impact. 

• Embed data science and analytics leadership into cross-functional squads focused on Engagement, Retention, and AI, ensuring content insights are integrated into subscriber, marketing, and business strategy. 

• Partner with data engineering to deliver the infrastructure, feature stores, and data products required to support the modeling and analytics roadmap. 

• Translate complex models and analyses into clear, concise, and actionable narratives and recommendations tailored to executive audiences, including reconciling often incomplete or conflicting inputs. 

• Foster a high-trust, high-impact, collaborative culture across the team, with strong client service orientation, communication discipline, and credibility at every level of the organization. Act as a neutral, expert third party in cross-functional debates, gaining alignment across creative, finance, business, technology, and marketing stakeholders while maintaining analytical rigor and objectivity. 

• Develop talent through coaching, mentoring, and structured leadership growth, building a bench of data science and analytics leaders capable of supporting Disney DTC's most strategic content decisions. 

Required Qualifications 

• 12+ years of experience in data science, analytics, or decision science roles, with 8+ years in leadership or management, ideally in media, entertainment, streaming, or technology. 

• Bachelor's degree in Data Science, Statistics, Computer Science, Mathematics, Economics, Analytics, Engineering, or a related quantitative discipline. 

• Deep experience in media and entertainment video content strategy, including exposure to content valuation, licensing, and global content investment decisions. 

• Proven track record building and scaling data science and analytics capabilities, including teams of data scientists, that directly support content, programming, or portfolio decisions in a content-led organization. 

• Experience leading the development of statistical and machine learning models at scale, including time series forecasting, survival analysis, segmentation and clustering, propensity models, and causal inference, and operationalizing them into production. 

• Deep knowledge of machine learning algorithms and advanced statistics, including forecasting business metrics, leading indicators, and feature importance. 

• Proven ability to architect and deliver multi-year data science and analytics roadmaps, including the models, tools, methodologies, and data products required to scale impact. 

• Experience translating complex data, models, and analytics into clear and actionable storylines for non-technical audiences (e.g., creative experts). 

• Experience leading cross-functional initiatives and gaining alignment across stakeholders with competing priorities. 

• Demonstrated ability to operate as a detective: spotting patterns across complex, disparate data sets and translating them into insights, models, methodologies, and frameworks that change decisions. 

• Strong fluency with data science and analytics tools (SQL, Python/R, statistical and ML platforms, Looker, Tableau) and modern data platforms (Databricks, Snowflake, AWS or equivalent). 

• Track record of executive communication and influence across technical and non-technical audiences, including the ability to engage with creative leadership, finance, and senior business executives with equal credibility. 

Preferred Qualifications 

• Graduate degree (M.S. or Ph.D.) in Data Science, Statistics, Computer Science, Mathematics, Economics, Engineering, Business, or a related quantitative discipline. 

• Prior leadership experience in streaming media and/or supporting a direct-to-consumer subscription business. 

• Knowledge of subscription models, engagement and retention dynamics, and content's role in the subscriber lifecycle. 

• Demonstrated financial impact delivered through data science applications and models in production. 

• Experience implementing Generative AI applications for data science and analytics use cases and workflows. 

• Experience with NLP methods (e.g., topic modeling, sentiment analysis) applied to audience, content, or survey data. 

• Direct relationship-building and analytics support experience with content studios (Film, TV) and content partnership functions, including licensing, currents, and other content deals. 

• Familiarity with international content strategy and the operational complexity of data science and analytics across global markets. 

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