TED Conferences, LLC

TED Conferences, LLC

Audience & Marketing Manager, Podcasts

New York, NY, United States · Contract

Sponsorship not specifiedDetected 43 days ago
SparkA/B TestingProject ManagementExcelCustomer SupportResearchCommunicationCollaborationProblem Solving

About the role

  • This role will be responsible for leading strategy and execution for a number of key priority shows, as well as supporting our team with the broader growth efforts across TED podcasts.
  • will include strengthening our audience strategy, driving listenership via the full slate of tools and placements, and translating performance data into growth action items.
  • This is a temporary grant-sponsored position with an end date of May 31, 2028.

Responsibilities

  • Own end-to-end marketing strategy and execution for a slate of priority TED podcasts
  • Utilize and optimize existing growth tools and placements, including audio cross-promotions, feed drops, host guest swaps, PR, paid, newsletter, social media and Web.
  • Manage a paid media budget, developing and executing a strategy to meet listeners on social media, YouTube and Search.
  • Build and iterate a growth roadmap informed by data, experimentation and audience insight.
  • Partner closely with PR teams and external partners to support press outreach and cultural moments, ensuring they have the assets and context needed to be effective (episode descriptions, host details, launch timelines, etc.).
  • Serve as a key point of connection between marketing, editorial, production, PR, analytics and platform partners for focus shows.
  • Act as a bridge between influencers, editorial partners, podcast guests and hosts, and the production process for focus shows - managing deliverables, communication and timelines.

Nice to have

  • Degree (preferred) or diploma in commerce, administration, communications or similar discipline, or similar experience.

Compensation

  • $80,000 - $82,000

This listing is sourced directly from TED Conferences, LLC's careers page and normalized into a canonical job model.