Lead Strategic Finance & Analytics Engineer

Klaviyo • Boston, MA

6h • $148,000 - $222,000

About The Position

Klaviyo is hiring a Lead Strategic Finance & Analytics Engineer to build and maintain production-quality models forecasting recognized revenue and cost of goods sold (COGS). The role combines data science, finance, and data engineering, beginning with recognized revenue forecasting and expanding to consumption-aligned infrastructure costs such as message sending and LLM usage, then the broader COGS base. The resulting systems will support planning, pricing, and margin analysis as Klaviyo's products increasingly use consumption-based models.

Reporting into Strategic Finance & Analytics, this hands-on technical role partners closely with FP&A, Product, Engineering, Data Science, Go-to-Market, and Analytics Engineering. The engineer owns models end to end, establishes standards for building and evaluating forecasts, and helps grow the team's capabilities. The work connects customer product usage to revenue and delivery costs, supports budgeting and long-range planning, and makes forecasting a trusted, repeatable company practice.

The position may require up to 10% travel for new-hire onboarding, client or partner work if applicable, team meetings, and industry events. Travel is coordinated in advance. The base salary range for U.S. locations is $148,000–$222,000 USD. Total compensation may include an annual cash bonus, equity, sign-on payments, and eligible health, welfare, and wellbeing benefits.

Requirements

• At least 8 years of experience in data science, analytics engineering, strategic finance, or a related quantitative field.
• Hands-on experience building and deploying forecasting models in production.
• Understanding of how revenue recognition, usage, pricing, and cost drivers translate into financial outcomes.
• Strong foundations in statistics and time series forecasting, with experience applying hierarchical, probabilistic, or machine-learning methods to business problems.
• High proficiency in SQL and Python or R, with experience building production-quality analytical solutions.
• Familiarity with dbt and modern analytics engineering practices.
• Experience with cloud data platforms and distributed processing systems.
• Experience with revenue, pricing, usage-based, or subscription data; SaaS or platform business experience is ideal.
• Comfort working with imperfect data definitions, evolving metrics, and tradeoffs between precision and decision usefulness.
• Ability to turn ambiguous business questions into defined analytical approaches, success metrics, and recommendations.
• Demonstrated technical leadership setting direction on complex projects and influencing standards across teams.
• Clear communication skills, including the ability to explain modeling decisions and tradeoffs to technical and non-technical audiences, including senior executives.
• AI-first mindset and curiosity about using LLMs and agentic tools to improve forecasting and analytical workflows.
• 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 Haves

• 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 for 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.

Responsibilities

• Build and maintain forecasting models for recognized revenue and COGS, starting with overall recognized revenue and extending to consumption-aligned costs and the broader COGS base.
• Connect product workloads and usage drivers, including message volume, profile growth, channel mix, and AI feature usage, to revenue and delivery costs.
• Build forecasts that scale across time horizons and levels of granularity and can be extended to new consumption-based products.
• Partner with Finance and FP&A to translate planning mechanics and modeling assumptions into documented frameworks for budgeting, rolling forecasts, and long-range planning.
• Monitor forecast performance by tracking accuracy and bias, detecting drift, and building challenger models.
• Lead variance investigations when actuals diverge from forecasts, distinguishing data issues, model limitations, customer behavior, pricing or product changes, and external factors.
• Run scenario and sensitivity analyses for pricing changes, product launches, vendor and infrastructure decisions, and cost-efficiency initiatives.
• Partner with Analytics Engineering on reliable pipelines and dbt models that provide a trusted foundation for forecasting.
• Establish technical standards for forecasting methodology, evaluation, and code quality.
• Communicate modeling insights and tradeoffs to technical and non-technical audiences, including Finance and Product partners and executive leadership, using visualizations, narratives, and presentations.
• Evaluate emerging techniques, including time series foundation models and AI-assisted workflows, where they can improve accuracy or speed.

Benefits

• Potential participation in the company's annual cash bonus plan.
• Equity may be included in total compensation.
• Sign-on payments may be included in total compensation.
• A comprehensive range of health, welfare, and wellbeing benefits based on eligibility.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior