Own and build production revenue forecasting end-to-end: model development, backtesting, deployment, monitoring, and iteration

Build forecasting systems that account for the dynamics of usage-based pricing, consumption patterns, and customer lifecycle across our cloud platform

Design and implement causal measurement frameworks to quantify the revenue impact of product launches, pricing changes, and GTM motions

Establish backtesting discipline and accuracy tracking as standing Finance metrics, making forecast quality visible and continuously improving

Contribute to shared analytics infrastructure and internal tooling that accelerates data science workflows across the organization

Translate model outputs into clear, actionable recommendations for Finance, Sales, and executive leadership

Partner with Data Engineering, Revenue Operations, and Product to build the feature pipelines and data foundations your models depend on

What You Bring Along:

Has an advanced degree in a quantitative discipline (Statistics, Mathematics, Computer Science, Physics, Economics) or equivalent depth through production experience

Hands-on experience building and deploying ML and statistical systems, with meaningful time spent on forecasting or causal inference in production

Has deep applied statistics foundations, including comfort with time-series methods, state-space models, hierarchical approaches, or causal inference techniques

Is highly proficient in Python and SQL, with experience productionizing models in cloud-scale data environments

Data Scientist, Finance Forecasting

Responsibilities

Benefits

Company

Clickhouse

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