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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.

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.

How You'll Make a Difference

Build and maintain forecasting models for recognized revenue and COGS. Start with overall recognized revenue, then extend to consumption-aligned infrastructure costs (message sending and LLM usage first) and, over time, the full COGS base, including cloud infrastructure, SMS and email carrier and vendor costs, AI inference, and support.
Connect product workloads to unit economics. Work with Engineering, Product, and Finance to link usage drivers (such as message volume, profile growth, channel mix, and AI feature usage) to both revenue and delivery costs.
Build forecasts that scale with the business across multiple time horizons and levels of granularity, designed to extend to new consumption-based products as they launch.
Partner with Finance and FP&A to understand planning mechanics and modeling assumptions, and translate them into robust, well-documented frameworks that feed budgeting, rolling forecasts, and long-range planning.
Monitor model performance over time, tracking accuracy and bias, detecting drift, and building challenger models to keep forecasts resilient.
Lead variance investigations when actuals diverge from forecast, separating data issues, model limitations, customer behavior, pricing or product changes, and external factors.
Run scenario and sensitivity analyses to evaluate pricing changes, product launches, vendor and infrastructure decisions, and cost-efficiency initiatives.
Partner with Analytics Engineering on reliable pipelines and dbt models that give forecasting a clean, trusted foundation.
Establish technical standards for forecasting methodology, evaluation, and code quality.
Communicate clearly to technical and non-technical audiences, from Finance and Product partners to executive leadership, through visualizations, narratives, and presentations.