Project Manager - Data Reporting and Visualization
New York, NY US
Comprised of Disney's international media businesses and the Company's various streaming services, the Direct-to-Consumer and International (DTCI) segment aligns technology, content and distribution platforms to expand the Company's global footprint and deliver world-class, personalized entertainment experiences to consumers around the world.
The Walt Disney Company's Direct-to-Consumer and International segment (DTCI) is a global, multiplatform media, technology and distribution organization for high-quality content created by Disney's Studio Entertainment and Media Networks groups.
DTCI includes Disney's international media operations and the Company's direct-to-consumer businesses globally, including the upcoming Disney-branded direct-to-consumer streaming service, the Company's ownership stake in Hulu, and the ESPN+ sports streaming service, programmed in partnership with ESPN. BAMTECH Media, developer of the ESPN+ and Disney-branded streaming platforms, oversees all consumer-facing digital technology and products across the Company as part of the Direct-to-Consumer and International segment.
The Marketing Analytics team is tasked with providing data and analytics support to marketing operations teams with a mission to drive new subscriber growth. The Data Analytics Manager will play a critical analytics role in supporting acquisition media channels including Paid Search, Display, Social, Video, Audio and Affiliate as well as non-paid media acquisition efforts. This individual will analyze complex data from both internal and external sources to help identify opportunities, inform media buying, optimize conversion funnels and ensure media dollars are optimally invested. The ideal candidate has a passion for digital and linear media landscapes and understands the intricacies and unique attributes of each step in the marketing funnel.
• Develop and maintain key analyses around our marketing funnel and subscriber LTV
• Mine internal user and response data to develop targeting models, decision rules and response forecasting
• Monitor and analyze performance data across channels, tactics, partners and individual ad networks to ensure budget is optimized
• Develop test and learn strategies related to targeting, creatives and other variables to improve end-to-end conversion throughout the funnel
• Support digital and linear marketing (social, display, search, audio, video and affiliate channels) to optimize channel performance, understand analytics needs
• Partner with internal data science and analytics teams to build and operationalize marketing science models
• Identify opportunities for data enhancement and appends utilizing internal and external resources
• 5+ years of experience within digital marketing and advanced data analytics
• Strong analytical skills with the ability to apply business strategy to data analysis and recommendations
• Expertise in digital media, web analytics and in-app systems including ad serving, tracking and reporting tools including DoubleClick, DART, Adobe Analytics, Kochava, Flashtalking, media platforms (DBM, Google Search, Adwords, Facebook, etc.)
• Excellent understanding of media fundamentals and industry knowledge, including media metrics, measurement and attribution
• Deep understanding of the underlying technology and algorithms behind each of our partner ad networks/platforms and how to optimize results
• 3+ years of work experience using SQL
• 3+ years of work experience using Python or R and other statistical programming language as well as experience writing, managing and deploying code
• Expertise manipulating large data sets, interpreting data trends and using a multitude of disparate data sources and tools
• Understanding of statistics concepts (e.g., hypothesis testing, regression analysis).
• Familiarity with business intelligence platforms and tools (e.g., Tableau, Looker, etc.)
• Experience in the streaming media industry or other subscription-based service
• Bachelor's degree in relevant focus (i.e., Computer Science, Data Science, Statistics or Machine Learning)