Vice President Data Science

VP, Data Science
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, data science and experimentation to help drive the streaming businesses forward. We are seeking an expert executive to take on the critical role of Vice President, Data Science as part of the DnA leadership team. This leader will provide technical and analytical leadership to their team and DTC in the development of a broad range of complex models and experimentation that support business needs for Disney Streaming. This role supports our broad range of streaming services (Disney+, Hulu, ESPN+) globally across domains and functions including operations, marketing, product & technology, content & programming, subscription & retention and streaming. Your primary responsibilities will include the development and implementation of predictive machine learning and AI models, propensity models, time series forecasting, segmentation, anomaly detection, fraud and commerce models, experimentation and causal inference.
Responsibilities:

• Build and lead a team of Data Scientists and Engineers that inform, influence, and support business priorities across projects and platforms using data to validate hypotheses and provide effectiveness/efficiency solutions.
• Be an instrumental leader in the planning and evolution of innovation in methodology, as well as be a future-focused voice in the tech and data space, internally and with partners.
• Develop and maintain strong relationships with executive leaders, partners and stakeholders to ensure impactful, positive business outcomes are prioritized.
• Approach model and project development from a client-focused process including needs assessment, requirements gathering, prototyping, UAT and partner engagement.
• 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 across functions and domains. Continuously improve existing and architect and prototype new models, working with data science and cross-functional engineering teams to operationalize models into production.
• Lead experimentation and testing across domains including test orchestration, prioritization, sizing and significance.
• Organize and prioritize data science roadmap in-line with business objectives. Translate product goals, OKRs and business problems into modeling and testing solutions, draw conclusions from data, and recommend actions.
• Function as an expert and collaborate with the team to assess how models and methods can be adjusted for better predictive power and accuracy.
• Proactively identify opportunities that can benefit from data science modeling and AI applications, roadmap, execute, present and implement for impact.
• Be the expert at utilizing data sources across the organization with ability to integrate data across multiple platforms where joins do not exist, account for missing data and pursue approaches to enhance and strengthen our data and feature store.
• Creatively solve problems with data, including collecting and analyzing data sets, developing insights, interpreting results, building appropriate models.
• 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.
• Spearhead the development and implementation of cutting-edge technologies and solutions that bring innovation/transformation to Streaming business challenges.

Qualifications:

• 15+ years of related professional experience and/or 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)
• Graduate degree in Information Management, Computer Science, Statistics, Mathematics, Engineering, Economics or equivalent professional experience
• Demonstrated experience with SQL.
• Experience with statistical / ML platforms (e.g., SAS, R, Python, JMP, Weka)
• Experience leading experimentation, testing and optimization.
• 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.
• Deep knowledge of machine learning algorithms, advanced statistics (time series forecasting, clustering algorithms, probabilistic models) and NLP (topic modeling, sentiment analysis).
• Outstanding business acumen, collaborative approach and client orientation in addition to strong technical skills
• Excellent communication and presentation skills to top executives
• Proven creative problem-solving, decision-making and critical thinking skills.
• Demonstrated outstanding interpersonal skills, including ability to partner with others and to lead multiple teams in a rapidly changing environment.
• Strong ability to simplify complex analytics into understandable stories and clear recommendations that are easily understood and executable

Preferred Qualifications:

• Deep knowledge of the streaming landscape and experience working in media and entertainment and subscription businesses
• Demonstrated financial impact via data science applications.
• Experience with Databricks

The hiring range for this position in California, New York, Washington is $298,200 to $399,900 per year. The base pay actually offered will take into account internal equity and also may vary depending on the candidate's geographic region, job-related knowledge, skills, and experience among other factors. A bonus and/or long-term incentive units may be provided as part of the compensation package, in addition to the full range of medical, financial, and/or other benefits, dependent on the level and position offered.