Executive Director, Data Science

Job Posting Title:

Executive Director, Data Science

Req ID:

10141575

Job Description:

Job Summary

Data Intelligence and Analytics (DnA) plays a crucial role at the center of the Disney Entertainment Direct to Consumer (DTC) business, supporting functions and teams with analytics and data science to help drive the streaming businesses forward. We are seeking a senior leader to provide technical and execution-focused leadership to the Data Science team within DnA in the development of complex models that support business needs for Disney Streaming.

This role supports our broad range of streaming services (Disney+, Hulu, ESPN DTC) globally across domains and functions including operations, marketing, product & technology, content & programming, subscription & retention. Your primary responsibilities will include the development and implementation of predictive machine learning and AI models, specifically focusing on propensity models, time series forecasting, and next best offer/action decisioning logic.

Responsibilities

Execution Leadership & Project Management

• Build and lead a team of Data Scientists that inform, influence, and support business priorities across projects and platforms using data to validate hypotheses and provide effectiveness/efficiency solutions.
• Manage the execution of the project roadmap, ensuring project delivery is in-line with business objectives and key results.
• Approach model and project development from a client-focused process including needs assessment, requirements gathering, prototyping, UAT and partner engagement.
• Proactively identify opportunities that can benefit from data science modeling and AI applications and manage the execution and implementation for impact.

Stakeholder Management

• Work effectively across multiple business units with numerous stakeholders to deliver advanced analytics and modeling solutions.
• Foster a culture of collaboration by developing cross functional partnerships with business units to ensure impactful, positive business outcomes are prioritized.
• Function as an expert and collaborate with the team to assess how models and methods can be adjusted for better predictive power and accuracy.
• Demonstrate outstanding interpersonal skills, including the ability to partner with others and to lead multiple teams in a rapidly changing environment.

Technical Implementation (Propensity, Forecasting & Decisioning)

• Lead the development of our predictive algorithms and machine learning applications across different areas with the aim of helping our stakeholders execute better, smarter and faster.
• Design and implement scalable frameworks for Next Best Action/Offer (NBA/NBO) decisioning, connecting propensity scores to optimal customer interventions.
• Continuously improve existing and architect and prototype new models, working with data science and cross-functional engineering teams to operationalize models into production.

Qualifications

• Bachelor’s degree in advanced mathematics, Statistics, Data Science or comparable field of study
• 12+ years of related professional experience
• Demonstrated financial impact via data science applications.
• Deep knowledge of machine learning algorithms and advanced statistics, specifically time series forecasting, probabilistic models, and decisioning/optimization algorithms.
• Experience with statistical / ML platforms and modern data ecosystems (e.g., Python, R, Databricks, Spark, PyTorch).
• Experience with forecasting business metrics, leading indicators and feature importance.
• Experience making complex and broad predictions based on a vast amount of past and/or present data through the development of statistical and/or machine learning models.
• Strong analytical and problem-solving skills to interpret data and draw conclusions.
• Outstanding business acumen, collaborative approach and client orientation in addition to strong technical skills.
• Strong ability to simplify complex analytics into understandable stories and clear recommendations that are easily understood and executable.

Preferred Qualifications

• Graduate degree in Information Management, Computer Science, Statistics, Mathematics, Engineering or equivalent professional experience.
• 12+ years of related professional experience and graduate-level academic training that includes coursework in relevant areas of science, data science, computer science or mathematics (including but not limited to statistics and probability).
• Deep knowledge of the streaming landscape and experience working in media and entertainment and subscription businesses.

<