Data Scientist, Finance Forecasting

About this role

Build and own revenue forecasting or causal measurement models for Anthropic’s Finance organization. Establish rigorous backtesting and accuracy tracking, and communicate model results to Finance and executive leadership.

About the company

Anthropic builds reliable and interpretable AI systems, including the Claude family of models, for businesses and developers. The company focuses on AI safety research and practical AI assistants for enterprise and consumer use.

The team

Finance Analytics and Business Intelligence team; Finance Forecasting team.

Stack

What you'll do

• Own production revenue forecasts or the causal measurement program for launches and events.
• Develop, deploy, backtest, and monitor models; use accuracy results to improve them.
• Contribute to research on event-aware forecasting, hierarchical reconciliation, and causal designs.
• Translate forecasts and model accuracy into recommendations for Finance and executives.
• Partner with the Analytics Engineer on feature pipelines, model deployment, and the forecast store.

What we're looking for

• Substantial data science, forecasting, or quantitative finance experience, including production model ownership.
• Strong Python and SQL skills, with experience productionizing models.
• Applied statistics expertise, with depth in production time-series forecasting or causal inference.
• Experience building backtesting and model accuracy-tracking practices.
• Experience presenting and defending forecasts or causal estimates to executives.
• Comfort working in an ambiguous, early-stage environment.

Nice to have

• Experience with exogenous-regressor or event-aware forecasting.
• Familiarity with hybrid or foundation-model forecasting systems.
• Pricing, elasticity, or marketing-mix modeling experience.
• Forecasting experience for a consumption-based or usage-billed business.