Data Scientist, Finance Forecasting

Details

Recognized on the 2025 Forbes Cloud 100 list, ClickHouse is one of the most innovative and fast-growing private cloud companies. With more than 3,000 customers and ARR that has grown over 250 percent year over year, ClickHouse leads the market in real-time analytics, data warehousing, observability, and AI workloads.

We’re on a mission to transform how companies use data. As we scale our cloud business, the decisions that shape pricing, capacity planning, and go-to-market strategy need to be grounded in rigorous quantitative modeling. We're hiring a founding Data Scientist to build ClickHouse's Finance forecasting and measurement capability from the ground up. You'll own forecasting models, causal measurement programs, and analytical frameworks that directly shape how leadership plans the business. You'll define the approach, build the infrastructure, and set the standard for how data science operates here.

This role is intended to be filled in the San Francisco Bay Area. The position is hybrid and is expected to go into the Menlo Park office 1-2x per week.

Responsibilities

• Own 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

Requirements

• 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
• Deep applied statistics foundations, including comfort with time-series methods, state-space models, hierarchical approaches, or causal inference techniques
• Highly proficient 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 (cloud, API, marketplace)
• Bias toward action in ambiguous, early-stage environments and comfort defining the problem as well as solving it
• Strong communication skills with executive stakeholders; able to translate complex modeling into actionable business recommendations
• Fluent with AI tools and workflows, including LLMs and AI coding assistants, and able to apply them effectively in analytical work
• Comfortable taking ownership of open-ended problems and building new functions from scratch

Compensation

The typical starting salary for this role in the US is $215,000 - $240,000 USD.

The typical starting salary for this role in US Premium Markets (e.g., San Francisco Bay Area, New York City Metro Area) is $239,000 - $267,000 USD.

These ranges reflect what we reasonably and in good faith believe to be the minimum and maximum pay for this role at the time of posting. The actual compensation may be higher or lower than the amounts listed and may be subject to future adjustments. Placement within the range depends on factors such as education, qualifications, experience, skills, location, performance, and business needs.

If you have any questions about compensation, contact [email protected].

Perks

• Flexible work environment — ClickHouse is globally distributed and remote-friendly
• Employer contributions towards healthcare
• Equity in the company (stock options)
• Flexible time off in the US; generous entitlement in other countries
• $500 home office setup for remote employees
• Global company gatherings and offsites

Equal Opportunity & Privacy

ClickHouse provides equal employment opportunities and prohibits discrimination and harassment of any type. See the ClickHouse applicant privacy notice for more information.