Walt Disney
Location
Santa Monica, CA | United States
Job description
The Subscriber Lifecycle Analytics team is looking for a Manager to lead the Commerce Analytics function supporting a growing ecosystem of Disney’s streaming service offerings (Disney+, Hulu, ESPN+). The broader Subscriber Lifecycle Analytics function partners closely with operational business teams to measure, understand, and take action to mitigate churn at key moments across the subscriber lifecycle with the Commerce Analytics team focused on payment failure-driven churn. Our team masters exploratory data analysis, advanced reporting, data modeling and visualizations that serve the dual purpose of driving business decision making and delivering fact-based actionable recommendations. This team collaborates cross-functionally across the Direct to Consumer organization as well as with stakeholders from business units across The Walt Disney Company to generate insightful, compelling, and strategic analysis and plans. This role will build strong relationships and partner closely with Product, Business Operations, Engineering, Analytics, and Data Science teams to execute on innovative methods and best-in-class practices that power all of our improvements. The team’s work will drive the development of business and operational plans that are expected to have broad influence at all levels of the organization.
Provide leadership and set strategic vision and direction for the Commerce Analytics team focused on billing, payments, and fraud
Manage relationship with stakeholders across the business, including but not limited to the Commerce Product and Engineering organizations
Partner closely with business stakeholders to develop short and long-term product roadmaps based on rigorous analytics
Lead A/B testing and experimentation analysis and support key business-critical product launches ensuring commerce flows and product features are optimized and functioning as expected
Support in day-to-day business operations through quick analytics and anomaly
Develop and maintain core business logic, data pipelines, and key metrics for measuring health of the billing, payment, and fraud products across Disney+, Hulu, and ESPN+
Oversee the development of operational dashboards in Looker and Tableau to understand performance over time, enable efficient exploratory analysis, and equip partners with self-serve tools
Drive team development through coaching, mentoring, training, and leadership growth
8+ years of relevant data analytics experience including domain expertise in the areas of commerce, billing, payments, and fraud
3+ years of experience managing teams of analysts
Proven track record of building and leading teams of analysts, data scientists, and data engineers
Extremely skilled at simplifying complex problems, distilling data, and constructing compelling narratives to guide decision making
Excellent relationship building and communication skills with all levels of the organization, from junior analysts to C-suite leaders
Expertise working with extremely large, disparate data sets and using SQL for data wrangling, designing ETLs, and analysis
Experience manipulating large data sets and interpreting data trends using a multitude of disparate data sources and tools
Experience building and scaling experimentation programs
Fluent in data exploration and visualization tools such as Looker and Tableau
Familiarity with advanced analytics methodologies such as anomaly detection, regression analysis, clustering, statistical inference, hypothesis testing, causal inference, and modeling techniques
Very comfortable translating highly technical analyses into easily understandable insights for non-technical stakeholders
Proven ability to rapidly grasp new technical systems and processes and partner effectively with highly technical product and engineering teams
Experience working with scripting languages such as Python or R
Experience in the streaming media industry and/or supporting a direct-to-consumer subscription-based product
Experience in the technology industry and knowledge of how to build and implement data products
Familiarity with data platforms and applications such as Databricks, Jupyter, Snowflake, Redshift, Airflow
Experience operating in an SDLC environment and deploying code
Bachelor’s degree in Computer Science, Engineering, Mathematics, Econometrics, Statistic or related degree
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