Data Scientist, Finance Forecasting

🕒 April 15

🏢🏡 San Francisco – Hybrid

💵 $215k - $240k / year

⏰ Full Time

🟡 Mid-level

🟠 Senior

📊 Data Scientist

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ClickHouse

WebsiteLinkedInAll Job Openings

51 - 200 employees

Founded 2016

☁️ SaaS

🏢 Enterprise

🤖 Artificial Intelligence

SaaS • Enterprise • Artificial Intelligence

ClickHouse is a fast and resource-efficient real-time data warehouse and open-source database that is designed to deliver superior query performance for mission-critical and time-sensitive applications. It is available as a cloud service on major platforms like AWS, GCP, and Azure, with a "Bring Your Own Cloud" option and a wide range of integrations for seamless operation within diverse tech stacks. ClickHouse excels in real-time analytics, machine learning, business intelligence, and observability, making it an ideal choice for tasks such as financial services, fraud detection, and gaming analytics. It supports developer-friendly SQL operations, offers cost-effective storage solutions, and provides an open-source alternative to traditional databases. Companies like Sony, Lyft, Cisco, GitLab, and Twilio leverage ClickHouse for its scalability, efficiency, and ease of use.

📋 Description

• 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

• 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 • Has worked with modern analytical platforms such as ClickHouse, Snowflake, BigQuery, or Spark • Has experience forecasting consumption-based or usage-billed businesses (cloud, API, marketplace) • Has a bias toward action in ambiguous, early-stage environments and is comfortable defining the problem, not just solving it • Communicates clearly with executive stakeholders and can translate complex modeling work into actionable business recommendations • Is fluent with AI tools and workflows, including LLMs and AI coding assistants, and applies them effectively in analytical work • Is comfortable taking ownership of open-ended problems and building new functions from scratch.

🏖️ Benefits

• Flexible work environment - ClickHouse is a globally distributed company and remote-friendly. We currently operate in over 20 countries. • Healthcare - Employer contributions towards your healthcare. • Equity in the company - Every new team member who joins our company receives stock options. • Time off - Flexible time off in the US, generous entitlement in other countries. • A $500 Home office setup if you’re a remote employee. • Global Gatherings – We believe in the power of in-person connection and offer opportunities to engage with colleagues at company-wide offsites.