Job Summary:Data Analysts in the Disney Streaming Engagement & Retention Analytics team are the analytics partner for the organization's Growth Marketing team. They support Disney’s streaming services through measurement, analysis, and insight generation. These analysts focus on helping our subscribers get the most value out of our services, and improving business results through the combination of statistical rigor, data analysis, and fast paced execution with an emphasis on driving actionable business recommendations.
Responsibilities:

• Goaling and KPIs: Work “full-stack” to define KPIs and goal metrics with XFN stakeholders, forecast outcomes, and measure pacing against those targets.
• Business Performance Reporting, Visualization, and Regression Management: Be the primary partner for cross-functional stakeholders to understand engagement and retention on the platform. When engagement is ahead or behind expectations, dig in to drive meaningful, actionable insights that help the business performance improve or double-down on success.
• ETL & Metric Design: Own metric design and creation by defining business requirements, framework & optimization, and long term data scalability.
• Deep-Dive Analysis: Analyze user behavior to identify patterns, uncover opportunities, and create a shared understanding of how our subscribers are engaging with the platform & content.
• Forecasting, and Opportunity Sizing: Both to set goals and help evaluate potential opportunities, this role will be tasked with forecasting and opportunity sizing. This will help business stakeholders evaluate trade-offs in different approaches, and create targets for driving business performance.
• Partnership: Partner closely with business stakeholders to identify and unlock opportunities, and with other data teams to improve platform capabilities around data modeling, testing platforms, data visualization, and data architecture.

Basic Qualifications:

• 5+ years of analytical experience.
• 4+ years work experience using SQL and Python/R or other statistical programming languages.
• Familiarity with data exploration and data visualization tools like Tableau, Looker, Chartio, etc.
• Understanding of statistics concepts (e.g., hypothesis testing, regression analysis).
• Ability to think strategically, analyze and interpret market and consumer information.
• Strong communication skills, as well as written and verbal presentation skills.
• Degree in an analytical field.