3 months ago

Data Scientist, Finance Forecasting

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 22 hours agoStatus: Live

Job Summary

Founding Data Scientist to build ClickHouse's Finance forecasting and measurement capability from the ground up, owning forecasting models, causal measurement programs, and analytics infrastructure. You’ll work across Finance, Sales, and Leadership to shape pricing, capacity planning, and GTM strategy with production ML solutions and actionable business recommendations.

Location: San Francisco

Workplace: Hybrid

Employment Type: Full time

Job Function: Data Science & Machine Learning

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

Pay and Benefits

Perks:Health InsuranceEquityRemote WorkTime OffHome OfficeGlobal Gatherings

Key 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
•Proficiency in Python and SQL, with experience productionizing models in cloud-scale data environments
•Experience with analytical platforms such as ClickHouse, Snowflake, BigQuery, or Spark
•Experience forecasting consumption-based or usage-billed businesses (cloud, API, marketplace)

Experience:CloudSaaSAnalyticsFinance

Education:Master's

Skills:CommunicationProblem-solving

Languages:English

Tech Stack:PythonSQLClickHouseSnowflakeBigQuerySpark

Company Brief

ClickHouse

Develops ClickHouse, a high-performance open-source columnar database for real-time analytics, enabling fast querying and processing of large volumes of data for analytics, monitoring, and business intelligence workloads.

Industry: Data Infrastructure

Headquarters: Menlo Park, United States

Founded: 2016

Website LinkedIn

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ClickHouse

3 months ago

Data Scientist, Finance Forecasting

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 22 hours agoStatus: Live

Job Summary

Location: San Francisco

Workplace: Hybrid

Employment Type: Full time

Job Function: Data Science & Machine Learning

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

Pay and Benefits

Perks:Health InsuranceEquityRemote WorkTime OffHome OfficeGlobal Gatherings

Key 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
•Proficiency in Python and SQL, with experience productionizing models in cloud-scale data environments
•Experience with analytical platforms such as ClickHouse, Snowflake, BigQuery, or Spark
•Experience forecasting consumption-based or usage-billed businesses (cloud, API, marketplace)

Experience:CloudSaaSAnalyticsFinance

Education:Master's

Skills:CommunicationProblem-solving

Languages:English

Tech Stack:PythonSQLClickHouseSnowflakeBigQuerySpark

Company Brief

ClickHouse

Industry: Data Infrastructure

Headquarters: Menlo Park, United States

Founded: 2016

Website LinkedIn