- Communicate sophisticated analyses and results to a wide array of business partners with varying technical expertise from operational teams to executive audiences, both in oral presentations and via written reports
- Partner closely with Commerce Product business team members to identify and unlock opportunities to combat global fraud and minimize risk
- Create and maintain operational dashboards in Looker and Tableau to understand performance over time, enable efficient exploratory analysis, and equip partners with self-serve tools
- Translate sophisticated business questions into SQL including accurate cohorting, calculations, filtering criteria and/or aggregations
- Understand the systems and business processes that populate critical systems with data
- Partner with Data Science teams to uplevel analyses using clustering/segmentation, regression modeling, and/or predictive modeling
- Bachelor's degree in Analytics, Computer Science, Statistics, Economics, Mathematics, or related field
- 5+ years of strategic analysis to advise product or business decision making
- 3+ years of hands-on analytical work experience with SQL (ETL ownership, sophisticated transformations, development of "analytical" datasets)
- Strong analytical skills with the ability to apply business strategy to data analysis and recommendations
- Ability to think strategically, analyze and interpret first and third party information
- Experience manipulating large data sets and interpreting data trends using a multitude of disparate data sources and tools
- Expertise with data exploration and data visualization tools like Tableau or Looker
- Strong analytical and technical skills to tackle issues, analyze the cause, quickly come-up with possible solutions, detail the changes, and communicate organizational impact
- Demonstrable experience in detailing the data requirements, data strategy, data rules (standardization, cleansing, and validation)
- Experience in the global billing, payments, and fraud domains
- Experience in A/B testing or other experimentation
- 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
- Bachelor's degree in Analytics, Computer Science, Statistics, Economics, Mathematics, or related field
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Senior Data Analyst - New York, United States - Disney Direct to Consumer
Description
About the Role & Team
The Subscriber Lifecycle Analytics team is looking for a Senior Data Analyst to join the Commerce Analytics function supporting global fraud analytics across Disney's streaming service offerings (Disney+, Hulu, ESPN+). The Commerce Analytics function partners closely with operational business teams to identify and mitigate fraudulent subscriber behavior as well as run experiments to improve the accuracy of fraud identification capabilities. Our team is responsible for exploratory data analysis, advanced reporting, data modeling and visualizations that drive business decision making. This role will build positive relationships and partner closely with Product, Engineering, and Data Science teams to complete 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 will have broad influence at all levels of the organization.
What You Will Do
Required Qualifications & Skills
Preferred Qualifications
Education
Additional Information
#DISNEYTECH
The hiring range for this position in Santa Monica, CA is $112,600 to $151,000, and in New York, NY is $118,000 to $158,200 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.