Data Scientist, Finance Forecasting

Details

ClickHouse is hiring a founding Data Scientist to build its Finance forecasting and measurement capability from the ground up. The role will own forecasting models, causal measurement programs, and analytical frameworks that inform pricing, capacity planning, go-to-market strategy, and business planning.

Responsibilities

• Own and build production revenue forecasting end to end, including model development, backtesting, deployment, monitoring, and iteration.
• Build forecasting systems that account for usage-based pricing, consumption patterns, and customer lifecycle across the ClickHouse cloud platform.
• Design and implement causal measurement frameworks to quantify the revenue impact of product launches, pricing changes, and go-to-market motions.
• Establish backtesting discipline and accuracy tracking as ongoing Finance metrics.
• 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 required by the models.

Requirements

• Advanced degree in a quantitative discipline such as Statistics, Mathematics, Computer Science, Physics, or Economics, or equivalent depth through production experience.
• Hands-on experience building and deploying machine learning and statistical systems, including meaningful production experience with forecasting or causal inference.
• Deep applied statistics foundations, including time-series methods, state-space models, hierarchical approaches, or causal inference techniques.
• High proficiency in Python and SQL, with experience productionizing models in cloud-scale data environments.
• Experience with modern analytical platforms such as ClickHouse, Snowflake, BigQuery, or Spark.
• Experience forecasting consumption-based or usage-billed businesses, such as cloud, API, or marketplace businesses.
• Bias toward action in ambiguous, early-stage environments and comfort defining problems independently.
• Clear communication skills, including the ability to translate complex modeling work into actionable business recommendations for executive stakeholders.
• Fluency with AI tools and workflows, including large language models and AI coding assistants, and the ability to apply them effectively in analytical work.
• Comfort taking ownership of open-ended problems and building new functions from scratch.

Compensation

The typical starting salary for US Premium Markets, including the San Francisco Bay Area, is $239,000–$267,000 USD per year. A standard US range of $215,000–$240,000 USD per year may apply in other locations.

Benefits

• Flexible work environment at a globally distributed, remote-friendly company operating in more than 20 countries.
• Employer contributions toward healthcare.
• Stock options for every new team member.
• Flexible time off in the US and generous entitlement in other countries.
• $500 home office setup benefit for remote employees.
• Opportunities to engage with colleagues at company-wide offsites.