The posting, in Klaviyo's own words
archived Nov 6, 2026At Klaviyo, we value the unique backgrounds, experiences and perspectives each Klaviyo (we call ourselves Klaviyos) brings to our workplace each and every day. We believe everyone deserves a fair shot at success and appreciate the experiences each person brings beyond the traditional job requirements. If you’re a close but not exact match with the description, we hope you’ll still consider applying. Want to learn more about life at Klaviyo? Visit klaviyo.com/careers to see how we empower creators to own their own destiny.
About the Team
Klaviyo's Strategic Finance & Analytics team helps leaders understand, measure, and plan for business performance. We work closely with Product, Engineering, Data Science, Go-to-Market, and Finance partners to turn complex data into financial insight that informs investment decisions, planning, and long-term growth. As Klaviyo expands its platform and launches new AI-powered products, more of our business is becoming consumption-based. That makes it increasingly important to connect what customers do on our platform to what we earn and what it costs us to deliver.
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About the Role
We're looking for a Lead Strategic Finance & Analytics Engineer to build and maintain the models that forecast Klaviyo's recognized revenue and cost of goods sold (COGS). This role blends data science, finance, and data engineering. You'll build scalable, production-quality forecasting systems, and you'll understand the financial mechanics well enough to make them useful for planning. The role starts with a focus on recognized revenue forecasting. From there, you'll build out COGS forecasts, beginning with consumption-aligned infrastructure costs such as message sending and LLM usage, and extending to the rest of our cost base. As more of our products move to consumption models, the systems you build will be the foundation for how we plan, price, and understand margin. You'll report into Strategic Finance & Analytics and partner closely with FP&A, Product, Engineering, Data Science, and Go-to-Market teams. This is a hands-on technical role. You'll own models end to end, set standards for how forecasts are built and evaluated, and help the team grow its capabilities.