Sr Analyst, Enterprise Operations

PayPal PayPal · Fintech · New York, NY +4 · Business Operations

This role focuses on building and maintaining dashboards, planning tools, and operational frameworks for PayPal's enterprise operational and annual planning process. It involves cross-functional collaboration with Finance, Business Units, and Operations teams to ensure data accuracy, automate reporting workflows, and provide leadership with timely, insight-driven visibility. The role requires strong analytical skills, attention to detail, and the ability to leverage analytics and AI-powered tools to improve and automate processes.

What you'd actually do

  1. Independently plan and execute operational processes.
  2. Collaborate internally to optimize workflows and drive process improvements.
  3. Influence the quality, efficiency, and effectiveness of business processes.
  4. Determine appropriate actions while considering alternative solutions.
  5. Provide oversight and support for planning and management of financial, budget, and headcount targets.

Skills

Required

  • 3+ years relevant experience and a Bachelor’s degree OR Any equivalent combination of education and experience.
  • Proven capability to think strategically, anticipate organizational needs, and shape long-term plans that align data, operations, and risk management objectives.
  • Strong analytical and problem-solving skills, with attention to detail and comfort working with structured data.
  • Effective communication and collaboration skills with comfortability working across multiple stakeholders.
  • Adaptable, “can do” mindset; eager to drive change and improvements in a fast-paced organization with evolving priorities.

Nice to have

  • Deep understanding of dashboarding and reporting tools (e.g. Power BI, Power Automate, etc.).
  • Data-driven approach, ability to leverage analytics and AI-powered tools to improve and automate processes and generate insights.
  • Demonstrated expertise in implementing and maintaining data governance frameworks, quality standards, and control mechanisms across complex data environments.

What the JD emphasized

  • AI-powered tools to improve and automate processes
  • data governance frameworks