Manager, Data Analytics - Subscriber Lifecycle Analytics

Key Skills

Business Strategy, Data Analytics, Data science techniques, Data Visualization, Databricks, Effective communication skills, Employee life cycle, ETL frameworks, Finance, Jupyter Notebook, Looker, Operations, SDLC, Snowflake, SQL, Tableau

Job Description

What You'll Do

• 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

Key Qualifications

• 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

Nice To Haves

• 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

Required Education

• Bachelor’s degree in Computer Science, Engineering, Mathematics, Econometrics, Statistic or related degree

The hiring range for this position in Santa Monica, CA is $136,100 to $182,400, and in New York, NY is $142,600 to $191,100 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.