Data & Analytics Product Operations Intern

Zoetis•Parsippany-Troy Hills, NJ
•$17 - $40

About The Position

Zoetis is seeking a Data and Analytics Product Operations Intern to support its Diagnostics Digital ecosystem by improving how product and business teams find, understand, trust, and use data. The intern will partner with Business and Technical Product Managers, Product Owners, and engineering teams to support analytics dashboards, define core data elements, and advance foundational data governance practices, including data cataloging, definitions, documentation, and data quality.

Requirements

  • Currently pursuing a Bachelor's degree from an accredited U.S. college or university, with an anticipated graduation date in 2027.
  • Demonstrated interest in analytics, data usability, and data governance, including concepts such as data definitions, data quality, metadata, and cataloging.
  • Strong written and verbal communication skills, with the ability to explain data concepts to technical and non-technical audiences.
  • Ability to collaborate effectively across business, product, data, and engineering teams.

Nice To Haves

  • Preferred areas of study include Business Analytics, Information Systems, Data Science, Computer Science, Industrial Engineering, Statistics, Applied Mathematics, or a related field.
  • Experience with or exposure to common analytics and business intelligence tools, such as Power BI, Tableau, and SQL.

Responsibilities

  • Support the development and maintenance of product and operational dashboards, including metrics related to adoption, workflow usage, reliability, and availability, in partnership with product and engineering teams.
  • Assist with data governance initiatives, including maintaining data catalog entries, business glossary terms, core data elements, and basic lineage and contextual documentation for key datasets.
  • Enable self-service analytics by developing how-to guides, facilitating training sessions and office hours, and helping product teams understand dashboard usage, data interpretation, and data literacy best practices.
  • Collaborate with data and engineering stakeholders to identify data gaps, including instrumentation, tagging, and missing fields, while tracking action items and supporting continuous improvement in data quality and usability.
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