Description
As an early member of Anthropic's Finance Analytics and Business Intelligence team, you will play a key role in building robust analytics engineering and business intelligence capabilities for the Finance & Accounting organization.
You will own revenue forecasting models that drive capacity planning and board reporting, build the backtesting and accuracy discipline that makes those forecasts trustworthy, and lead causal measurement work that tells us how much a given launch or event actually moved revenue.
Key responsibilities:
- Own a core piece of the team's modeling work , either the production revenue forecasts themselves or the causal measurement program for launches and events
- Build and run backtesting and accuracy tracking for your models, and use the results to improve quality cycle over cycle
- Contribute to the team's broader research direction, including event-aware forecast architectures, hierarchical reconciliation, and causal designs that hold up under launch-driven step-changes
- Translate model output and accuracy results into clear recommendations for Finance and executive leadership
- Partner with the team's Analytics Engineer on feature pipelines, model deployment, and the forecast store
Minimum qualifications:
- Substantial experience in data science, forecasting, or quantitative finance
- Fluency in Python and SQL
- Strong applied statistics foundation, with depth in either production time-series methods or causal inference
- Experience building backtesting and accuracy-tracking discipline
- Presented and defended a forecast or causal estimate to executives
Preferred qualifications:
- Experience with exogenous-regressor or event-aware forecasting approaches
- Familiarity with hybrid or foundation-model forecasting
- Background in pricing and elasticity modeling or marketing-mix modeling
- Experience forecasting a consumption-based or usage-billed business
The annual compensation range for this role is $270,000-$345,000 USD.