TelevisaUnivision

TelevisaUnivision

Senior Analyst, Content Partnerships

Miami, FL · Senior

Sponsorship not specifiedDetected 21 hours ago
Data VisualizationStatisticsContent MarketingNegotiationExcelResearchCommunicationCollaborationProblem Solving

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odds of building a lasting career here

37Risky
Cap-exempt (no lottery)0
Sponsors this role80
Entry-level history0
PERM / green-card track0
Lottery odds40
Fits your clock70

Thin sponsorship signal and lottery-bound. A low-probability bet with your clock running. Prioritize cap-exempt roles and proven entry-level sponsors first.

Lottery odds assume a STEM candidate.

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About the role

  • You are extremely passionate about Spanish-language content, highly analytical, well organized, and a strong communicator.
  • You are comfortable in a high-volume, fast-paced environment, while navigating across various teams and processes.
  • TelevisaUnivision is an equal opportunity employer.

Nice to have

  • Analyze data gathered from internal and external sources to maximize efficiency and understanding of business success and customer satisfaction based thereon.
  • Analyze the competitive environment and identify digital and independent content providers to better position content offerings and recommend acquisition strategies.
  • Assess contractual rights, linear and nonlinear programming schedules, and financial processes integrated via internal systems.
  • Review upcoming schedules to identify potential delivery and operational issues, including programming start and expiration dates for programming.
  • Bachelor's degree or equivalent in Marketing, Analytics, or related field, plus 2 years of experience in the occupation or as a business intelligence analyst.
  • 2+ years' experience in Spanish language cable, broadcast or streaming platforms.
  • Experience with business intelligence tools such as Power BI, Tableau, or advanced Excel.
  • Experience managing complex datasets across multiple geographies.

This listing is sourced directly from TelevisaUnivision's careers page and normalized into a canonical job model.