The Subscriber Lifecycle vertical is looking for a Lead Data Analyst to join the Commerce Analytics team supporting global commerce experimentation across Disney’s streaming service offerings (Disney , Hulu, ESPN ). The Commerce Experimentation Analytics function partners closely with Product Managers to test opportunities to minimize involuntary churn by reducing payment failures and improving payment recovery. This role will build strong relationships and partner closely with Product, Engineering, 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.

Responsibilities

• Communicate complex analyses and results to a wide array of business stakeholders with varying technical expertise from operational teams to executive audiences, both in oral presentations and via written reports

• Partner closely with the business and payments engineering partners to support Commerce A/B experimentation end-to-end: experimental design, metric definition, power analysis, QA, experiment launch support and monitoring, and communicating experiment results and recommendations

• Partner closely with Commerce Product business stakeholders to identify and unlock opportunities to improve front-end payment funnels, backend payment processing strategy, and subscriber recovery strategy; combat global fraud and minimize risk

• Develop and maintain ETL pipelines using SQL and python to automate reporting, share high-level insights, and equip partners with self-serve tools

• Identify business-critical changes in payment health using anomaly detection methods

• Translate complex business questions into SQL including proper cohorting, calculations, filtering criteria and/or aggregations

• Partner with Data Science teams to uplevel analyses using clustering/segmentation, regression modeling, and/or predictive modeling

Required Qualifications

• Bachelor’s degree in Data Science, Analytics, Computer Science, Statistics, Mathematics, or related field

• 7 years of strategic analysis to inform product or business decision making

• 3 years of hands-on analytics work experience with A/B testing and statistical analysis

• Ability to draw insights and conclusions from data to inform model development and business decisions

• Desire to collaborate with other data scientists, data analysts, engineers, and key business partners

• Proficient in analyzing data and developing models using Python

• Experience operationalizing and fully integrating models into business operations

• Strong analytical skills with the ability to apply business strategy to data analysis and recommendations

Desired Qualifications

• MS or PhD in Data Science, Analytics, Computer Science, Statistics, Mathematics, or related field

• Experience in the global billing, payments, and fraud domains

• Experience in the streaming media industry and/or supporting a direct-to-consumer or subscription-based product

• Experience in the technology industry and knowledge of how to build and implement data products