Product Cost Analyst

Cloudflare•San Francisco, CA

1d•$110,000 - $174,000

About The Position

Cloudflare is seeking a Financial Analyst to join its R&D Finance team and explain the costs of building, delivering, and scaling its products. The role partners with Product, Engineering, Infrastructure Finance, Pricing, Accounting, and finance data partners to convert technical resource usage and infrastructure investment into clear product unit economics and actionable financial insights. It is a hands-on individual contributor position involving financial models, operational data, cross-functional problem solving, and improving finance data and processes through automation and thoughtful use of AI. There is an opportunity to deepen ownership of Developer and self-serve product economics as the work evolves. The analyst builds product cost models for compute, storage, bandwidth, and AI/inference resources; evaluates cost and margin impacts of product and architecture changes; develops shared-cost allocation analyses; and supports pricing, capital planning, and forecasting. The role connects infrastructure investments and capacity decisions to product economics and produces decision-ready reporting that explains cost, margin, and actual-versus-plan changes. It also improves data quality, reconciliations, controls, and recurring workflows to support more frequent forecasting and a faster, more reliable close. The position is available in Austin, San Francisco, Denver, or Seattle. Compensation varies by location. The role is eligible for Cloudflare’s equity plan and employee benefits. Applicants progressing to the offer stage may be asked to attend an in-person interview at a Cloudflare office or hub. The role may require access to information protected under U.S. export control laws; an offer may be conditioned on authorization to receive controlled software or technology without sponsorship for an export license.

Requirements

At least 5 years of experience in FP&A, strategic finance, cost analysis, business analytics, or a related analytical field, with evidence of building financial models and translating data into business recommendations.
Advanced Excel or Google Sheets skills, including building flexible, driver-based models and testing assumptions through sensitivity and scenario analysis.
Ability to work with large or imperfect datasets, investigate discrepancies, reconcile financial and operational views, and document assumptions and controls.
Understanding of financial statements, cost drivers, gross margin, and unit economics, with familiarity with capital expenditures and depreciation.
Ability to learn technical business models and connect resource usage, infrastructure capacity, and product architecture to financial outcomes.
Strong cross-functional collaboration and clear written and verbal communication; comfortable asking questions, constructively challenging assumptions, and explaining analysis to different audiences.
Evidence of ongoing AI skill development, including prompt and context engineering; ability to evaluate emerging tools and apply them to practical finance problems.
Bachelor’s degree in Finance, Accounting, Economics, a related quantitative field, or equivalent practical experience.

Nice To Haves

Experience with cloud infrastructure, developer platforms, usage-based businesses, product costing, or shared-cost allocations.
Hands-on SQL skills and experience with business intelligence tools; Python or another analytical scripting language for repeatable analysis.
Familiarity with infrastructure and/or data-center operations and the financial drivers of capacity expansion, such as hardware, power, cooling, and deployment lead times; exposure to construction or build-out economics is a plus.
Exposure to server or network capital planning, hardware lifecycle economics, utilization analysis, or fixed-asset reporting.
Demonstrated ability to integrate AI tools into finance or analytical workflows—such as data preparation, reconciliation, cost-model updates, or variance analysis—with measurable improvements in cycle time, accuracy, or review quality.
Experience applying responsible AI practices to financial analysis, including assessing data-privacy and decision risks, checking for bias or misleading assumptions, validating outputs against source data, and maintaining human review and an auditable record.
Experience improving financial systems, allocation processes, data pipelines, or forecasting workflows in a matrixed organization.
Familiarity with planning and enterprise systems such as Anaplan, Oracle, or Workday.

Responsibilities

Build and maintain product cost models translating compute, storage, bandwidth, and AI/inference resource consumption into unit cost-to-serve, with transparent assumptions and documented methodologies.
Partner with Product and Engineering to assess new product introductions, architecture changes, and changes in resource usage; quantify cost and margin implications across connected workloads.
Develop and validate shared-cost allocation analyses with Infrastructure Finance and finance data partners using relevant consumption and capacity drivers.
Distinguish direct costs, shared costs, and unused capacity, and reconcile product views to underlying financial totals.
Support Pricing with reliable cost inputs and scenario analysis for commercial decisions and quoting workflows.
Update assumptions to reflect changes in hardware generations, bandwidth rates, and product architecture.
Analyze server costs, deployment timing, useful-life and depreciation assumptions, utilization, and capacity across edge, core, and accelerated-computing infrastructure, in partnership with Infrastructure Finance and Accounting.
Contribute to capital and capacity planning through demand-versus-capacity scenarios, investment trade-offs, and forecast updates.
Explain how deployment timing and workload mix affect near-term costs and longer-term unit economics.
Produce decision-ready reporting on product costs, unit economics, and relevant margin drivers.
Explain actual-versus-plan changes and distinguish volume, mix, rate, utilization, and allocation effects.
Improve finance data and repeatable workflows with finance programs, data, and engineering partners.
Validate operational inputs, establish reconciliation checks, and automate recurring analyses to support more frequent forecasting and a faster, more reliable close.
Translate analysis into actionable recommendations for technical and non-technical partners, balancing detail, financial judgment, and the needs of a growing product portfolio.

Benefits

Medical/Rx insurance
Dental insurance
Vision insurance
Flexible Spending Accounts
Commuter Spending Accounts
Fertility and family-forming benefits
On-demand mental health support and Employee Assistance Program
Global Travel Medical Insurance
Short- and long-term disability insurance
Life and accident insurance
401(k) Retirement Savings Plan
Employee Stock Participation Plan
Flexible paid time off covering vacation and sick leave
Leave programs, including parental, pregnancy health, medical, and bereavement leave
Equity plan eligibility