Klaviyo Lead Strategic Finance & Analytics Engineer at Klaviyo building forecasting models for recognized revenue and COGS. Connects product usage to financial metrics to support planning and pricing.
Responsibilities
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.
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.
Qualification
You have experience with revenueYou have a degree in StatisticsExperience forecasting COGSExperience supporting FP&AWhy This Role Matters
Required
You have 8+ years of experience in data science, analytics engineering, strategic finance, or a related quantitative field, with hands-on experience building and deploying forecasting models in production.
You combine technical depth with finance context. You understand how revenue recognition, usage, pricing, and cost drivers translate into financial outcomes.
You have strong foundations in statistics and time series forecasting, and experience applying methods such as hierarchical, probabilistic, or machine learning approaches to business problems.
You're highly proficient in SQL and Python or R, with experience building production-quality analytical solutions, and you're familiar with dbt and modern analytics engineering practices.
You've worked with cloud data platforms and distributed processing systems.
You have experience with revenue, pricing, usage-based, or subscription data, ideally in SaaS or a platform business.
You're comfortable with imperfect data definitions, evolving metrics, and tradeoffs between precision and decision usefulness.
You can turn ambiguous business questions into well-defined analytical approaches, success metrics, and clear recommendations.
You've demonstrated technical leadership by setting direction on complex projects and influencing standards across teams.
You're a clear communicator who can explain modeling decisions and tradeoffs to both technical and non-technical audiences, including senior executives.
You bring an AI-first mindset and are curious about how LLMs and agentic tools can improve forecasting and analytical workflows.
You have a degree in Statistics, Mathematics, Computer Science, Economics, Finance, Engineering, or another quantitative field, or an advanced degree with a quantitative emphasis. Equivalent hands-on experience is equally valued.
Preferred
Experience forecasting COGS, cloud or infrastructure costs, or other unit-cost drivers.
Experience with consumption-based or usage-based pricing models.
Experience supporting FP&A, strategic finance, or investor-facing analysis.
Experience building self-service dashboards or forecasting tools used by Finance and Product partners.
Experience establishing forecast evaluation frameworks or governance practices.
Hands-on exposure to time series foundation models, LLMs, or agentic AI for forecasting and decision support.
Why This Role Matters
Accurate revenue and COGS forecasts are the foundation for how Klaviyo plans investments, prices new products, and manages margin. As our portfolio adds consumption-based products, the ability to connect customer usage to revenue and delivery cost will become one of the most important inputs to our decisions. In this role, you'll build that capability from the ground up and help make forecasting a trusted, repeatable practice across the company.
