Sr. Financial Analyst / Manager - R&d Finance & Finops

Zapier Zapier · Enterprise · NAMER · Finance

This role supports the R&D organization by partnering with Product, Engineering, and Infrastructure leaders to drive financial accountability, improve investment visibility, and enable better decision-making across the R&D portfolio. The role involves financial planning and analysis for R&D spend, modeling cloud and infrastructure economics, analyzing AI investments, and supporting executive reporting. The candidate should have experience partnering with R&D teams and understanding technical roadmaps.

What you'd actually do

  1. Own R&D financial planning and analysis. Lead forecasting, budgeting, and variance analysis for R&D spend, including headcount, cloud infrastructure (AWS), tooling, and AI-related costs.
  2. Model and manage cloud & infrastructure economics. Build and maintain models that explain cloud costs, key usage drivers, unit economics, and scaling behavior; partner with technical teams to improve cost visibility and efficiency.
  3. Analyze and support AI investments. Evaluate and track AI-related spend (internal and vendor-based), assess ROI and trade-offs, and support decision-making as AI usage scales across the product and internal operations.
  4. Drive strategic insights for R&D leadership. Identify trends, risks, and optimization opportunities across R&D spend, translating complex cost drivers into clear recommendations for leadership.
  5. Develop scalable, decision-ready models. Build flexible models to support scenario planning, capacity planning, and long-term investment decisions tied to product growth and technical architecture.

Skills

Required

  • 4-6+ years of accounting/finance-specific experience
  • 2+ years of working with R&D orgs
  • Financial modeling
  • Understanding of modern R&D organizations
  • Ownership of a process from A-Z
  • Data analysis
  • Detail-oriented
  • Collaboration and coordination
  • Experience with AI tools and their application in finance

Nice to have

  • Big 4 Accounting, Investment Banking, or Management Consulting background
  • Experience with R&D or technical cost structures
  • SQL

What the JD emphasized

  • partner closely with Product, Engineering, and Infrastructure leaders
  • drive financial accountability
  • improve investment visibility
  • enable better decision-making
  • finance partner to R&D or product teams
  • translate technical roadmaps into financial frameworks
  • board materials, competitive intelligence, and strategic planning
  • 4-6+ years of accounting/finance-specific experience
  • 2+ years of working with R&D orgs
  • background in Big 4 Accounting, Investment Banking, or Management Consulting
  • meaningful ownership of operating expense areas
  • R&D or technical cost structures
  • understand financial modeling well
  • experience building bottoms up and high level financial models
  • understand how modern R&D organizations operate
  • translate engineering, product, and infrastructure inputs into clear financial implications and trade-offs
  • energized by owning a process from A-Z
  • take initiative, thrive in ambiguity, and enjoy seeing things through from scoping and modeling to execution and follow-through
  • resourceful
  • love a challenge and always question the status quo
  • highly adaptive and enjoy getting creative to solve new problems
  • love data
  • innately curious, analyze everything, look for trends, and always forever truth-seeking
  • care about the nitty gritty
  • detail-oriented, highly organized, understand priorities, and thrive in a fast paced environment
  • love to collaborate and coordinate
  • comfortable driving cross-functional alignment and take pride in delivering high-quality work with minimal oversight
  • actively experiment with AI
  • think critically about where automation and AI can meaningfully improve financial analysis, forecasting, and decision support
  • use AI in your work today — not occasionally, but as part of how you operate at a high level
  • can point to workflows you’ve built, how your approach has evolved through iteration, and the impact on quality, efficiency, and experience — while intentionally applying AI for the right outcomes, setting a high bar for outputs, and taking ownership of what ships
  • Lead forecasting, budgeting, and variance analysis for R&D spend
  • cloud infrastructure (AWS)
  • tooling
  • AI-related costs
  • Model and manage cloud & infrastructure economics
  • explain cloud costs, key usage drivers, unit economics, and scaling behavior
  • partner with technical teams to improve cost visibility and efficiency
  • Analyze and support AI investments
  • Evaluate and track AI-related spend (internal and vendor-based)
  • assess ROI and trade-offs
  • support decision-making as AI usage scales across the product and internal operations
  • Drive strategic insights for R&D leadership
  • Identify trends, risks, and optimization opportunities across R&D spend
  • translating complex cost drivers into clear recommendations for leadership
  • Develop scalable, decision-ready models
  • Build flexible models to support scenario planning, capacity planning, and long-term investment decisions tied to product growth and technical architecture
  • Support executive and board-level reporting
  • Prepare clear, concise materials that explain R&D performance, cloud and AI cost dynamics, and forward-looking implications for company strategy
  • Improve tools, processes, and data quality
  • Enhance forecasting accuracy
  • automate reporting where possible
  • improve how R&D, cloud, and AI cost data flows into FP&A systems