Senior Financial Analyst- R&d Fp&a (finops & Product) - West

Smartsheet Smartsheet · Seattle · United States · Finance

This role is a Senior Financial Analyst focused on R&D FP&A and FinOps for a software company. The primary responsibility is to partner with Engineering and Product organizations to manage and optimize cloud infrastructure costs, including AI/ML inference costs, and to evaluate the financial impact of new product features, particularly AI-driven ones. The role involves strategic forecasting, driving infrastructure FinOps excellence, optimizing unit economics, and building financial models for new product ROI. While the company develops AI capabilities, this role is finance-focused, managing the financial aspects of these operations rather than building the AI models themselves.

What you'd actually do

  1. Own the end-to-end rolling forecast for R&D, focusing specifically on cloud consumption, AI/ML inference costs, and headcount scaling
  2. Act as a core member of the FinOps practice, translating complex AWS/Azure/GCP usage data into actionable business insights
  3. Partner with Engineering to define and track Cost per User or Consumptions based cost, identifying opportunities to improve gross margins through architectural efficiency
  4. Lead monthly "Cloud Reviews" with Engineering VPs to analyze usage trends, Reserved Instance (RI) / Savings Plan coverage & waste reduction
  5. Build models to evaluate the ROI & margin impact of new features (e.g., AI) ensuring our innovation in automation remains profitable

Skills

Required

  • 5+ years of progressive experience and demonstrated growth in Finance/FP&A positions
  • Bachelor's degree in finance, accounting or economics
  • Excellent verbal & written communication skills with the ability to facilitate discussions with leaders
  • Analytical mindset and proficiency in building complex financial models
  • Experience with cloud-native cost management tools (e.g., CloudHealth, Apptio Cloudability, or AWS Cost Explorer)
  • Understanding of cloud cost components (compute, storage, data transfer) and their P&L impact

Nice to have

  • Experience with AI/ML inference costs
  • Experience with FinOps
  • Experience with R&D FP&A
  • Experience with AI-driven capabilities financial modeling
  • Experience with multi-cloud environments financial management
  • Experience with unit economics optimization
  • Experience with ROI and margin impact analysis for new features
  • Experience with process automation using AI & BI tools

What the JD emphasized

  • AI/ML inference costs
  • cloud infrastructure
  • AI-driven capabilities
  • multi-cloud environments
  • AWS/Azure/GCP usage data
  • architectural efficiency
  • AI