The posting
At 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.
About the Role
We're looking for a Lead Analyst 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.
- Evaluate emerging techniques, including time series foundation models and AI-assisted workflows, where they improve accuracy or speed.
Who You Are
- 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.
Nice to Have
- 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.
Massachusetts Applicants: It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability.
Our salary range reflects the cost of labor across various U.S. geographic markets. The range displayed below reflects the minimum and maximum target salaries for the position across all our US locations. The base salary offered for this position is determined by several factors, including the applicant’s job-related skills, relevant experience, education or training, and work location.
In addition to base salary, our total compensation package may include participation in the company’s annual cash bonus plan, variable compensation (OTE) for sales and customer success roles, equity, sign-on payments, and a comprehensive range of health, welfare, and wellbeing benefits based on eligibility.
Your recruiter can provide more details about the specific salary/OTE range for your preferred location during the hiring process.
Base Pay Range For US Locations:
$148,000—$222,000 USD
This role may require up to 10% travel for purposes such as new hire onboarding, client or partner work if applicable, team meetings, and industry events. Travel is coordinated in advance.
Get to Know Klaviyo
We’re Klaviyo (pronounced clay-vee-oh). We empower creators to own their destiny by making first-party data accessible and actionable like never before. We see limitless potential for the technology we’re developing to nurture personalized experiences in ecommerce and beyond. To reach our goals, we need our own crew of remarkable creators—ambitious and collaborative teammates who stay focused on our north star: delighting our customers. If you’re ready to do the best work of your career, where you’ll be welcomed as your whole self from day one and supported with generous benefits, we hope you’ll join us.
AI fluency at Klaviyo includes responsible use of AI (including privacy, security, bias awareness, and human-in-the-loop). We provide accommodations as needed.
By participating in Klaviyo’s interview process, you acknowledge that you have read, understood, and will adhere to our Guidelines for using AI in the Klaviyo interview Process. For more information about how we process your personal data, see our Job Applicant Privacy Notice.
Klaviyo is committed to a policy of equal opportunity and non-discrimination. We do not discriminate on the basis of race, ethnicity, citizenship, national origin, color, religion or religious creed, age, sex (including pregnancy), gender identity, sexual orientation, physical or mental disability, veteran or active military status, marital status, criminal record, genetics, retaliation, sexual harassment or any other characteristic protected by applicable law.
IMPORTANT NOTICE: Our company takes the security and privacy of job applicants very seriously. We will never ask for payment, bank details, or personal financial information as part of the application process. All our legitimate job postings can be found on our official career site. Please be cautious of job offers that come from non-company email addresses (@klaviyo.com), instant messaging platforms, or unsolicited calls.
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