Sr. Analyst, Strategic Initiatives

Our Direct-to-Consumer (DTC) portfolio is a powerhouse collection of consumer-first brands, supported by media industry leaders, Comcast, NBCUniversal and Sky. When you join our team, you’ll work across our dynamic portfolio including Peacock, NOW, Fandango, SkyShowtime, Showmax, and TV Everywhere, powering streaming across more than 70 countries globally. And the evolution doesn’t stop there. With unequalled scale, our teams make the most out of every opportunity to collaborate and learn from one another. We’re always looking for ways to innovate faster, accelerate our growth and consistently offer the very best in consumer experience. But most of all, we’re backed by a culture of respect. We embrace authenticity and inspire people to thrive. This position sits within Media Group Decision Sciences, a team with a charter to provide valuable insights that enable decision-making across NBCU’s TV networks, FAST channels, and Peacock. The role will traverse the many distribution avenues that put NBCUniversal’s content on screen in front of audiences. Key areas of focus include strategy for the company’s portfolio of FAST channels, as well as opportunistic partnership evaluation in streaming. Responsibilities FAST channel strategy: assess portfolio performance, track the competitive landscape, evaluate new opportunities, create materials for leadership updates, and coordinate across teams Competitive streaming insights: become a subject matter expert on the streaming landscape, leveraging multiple data sources to track key industry KPIs and helping troubleshoot issues with relevant data sources as they arise Contribute to ad hoc partnership evaluation using expertise in video landscape dynamics and impact across distribution platforms Produce quarterly earnings recaps that focus on competitor streaming services, to be shared across the company Prepare and contribute to executive-level presentations related to industry trends and ad hoc analysis Collaborate on analyses that involve querying large first, second, and third party datasets