Product Operations Manager- Global Intelligence

Uber Uber · Consumer · New York, NY +1 · Product

This role focuses on product operations for Uber's Global Intelligence, managing external data providers, guiding reporting and research projects, spearheading competitive strategy initiatives, optimizing the consumer experience using business metrics and competitive insights, developing rollout plans, and driving strategic planning. It requires data analysis, statistical analysis, econometric modeling, and project management skills.

What you'd actually do

  1. Oversee Uber’s company wide relationships with external data providers and research agencies, including budgeting and procurement.
  2. Guide team that translates externally collected data into regular reporting and ad hoc research projects for Uber’s executive & senior leadership teams (Sr Directors, Vice Presidents and Executives).
  3. Spearhead cross-functional teams for any initiatives that focus on competitive strategy and benchmarking for Uber globally.
  4. Leverage business metrics and competitive insights to optimize the end-to-end consumer experience and guide product improvements.
  5. Develop and manage comprehensive rollout plans, ensuring execution across regions and alignment of functional stakeholders.

Skills

Required

  • Bachelor's degree in Computer Science, Economics, Applied Mathematics, Engineering (any), Data Science, Business Administration, or a related field, plus five (5) years of progressive, post-baccalaureate experience in the job offered or a product operations-related occupation.
  • Performing data analysis using Google Sheets, Microsoft Excel, and Looker.
  • Conducting statistical analyses, including descriptive statistics, correlation, regression, and confidence interval estimation.
  • Building and interpreting econometric models using R and Python.
  • Utilizing project management frameworks and tools, including Jira, Asana, Airtable, or Microsoft Project.

Nice to have

  • Analyzing user requirements, procedures, and problems to automate or improve existing machine learning systems
  • Designing and implementing large scale customer experiments and Familiarity with experimentation techniques, including simulation or A/B testing
  • Developing relevant metrics and KPIs to measure performance by product teams.

What the JD emphasized

  • progressive, post-baccalaureate experience
  • Analyzing user requirements, procedures, and problems to automate or improve existing machine learning systems
  • Designing and implementing large scale customer experiments and Familiarity with experimentation techniques, including simulation or A/B testing