Über
As a founding Data Scientist on the Finance Forecasting team, you’ll own revenue forecasting models that drive capacity planning and board reporting, develop backtesting and accuracy discipline, and lead causal measurement work that quantifies how launches or events move revenue. We’re hiring for two seats and expect candidates to lead with depth in production time‑series forecasting or causal inference; tell us which you prefer. This is a build role on a small team where your forecasts are visible company‑wide and directly influence decisions.
Responsibilities
Own a core piece of the team's modeling work—either production revenue forecasts or the causal measurement program for launches and events.
Build and run backtesting and accuracy tracking for your models, using 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.
You May Be a Good Fit If You
Have substantial experience in data science, forecasting, or quantitative finance, including time owning models in production rather than only in notebooks.
Are deeply fluent in Python and SQL and comfortable productionizing what you build.
Have a strong applied statistics foundation, with depth in either production time‑series methods or causal inference techniques.
Have built backtesting and accuracy tracking discipline before and are comfortable having your models scored publicly.
Have presented and defended a forecast or causal estimate to executives.
Have a bias for action and do your best work in ambiguous, early‑stage environments.
Strong Candidates May Also Have
Experience with exogenous‑regressor or event‑aware forecasting approaches.
Familiarity with hybrid or foundation‑model forecasting (TimeGPT‑class systems).
Background in pricing and elasticity modeling or marketing‑mix modeling.
Experience forecasting a consumption‑based or usage‑billed business (cloud, API, marketplace).
What Success Looks Like in Your First Year
A cross‑methodology accuracy baseline is published as a standing Finance metric.
The base revenue forecast is measurably more accurate than today's consensus on the same out‑of‑sample window.
Launch incrementality is a standing readout with a designed, backtested method behind it.
Forecasts are queryable from the forecast store and feeding capacity planning and board reporting.
Things to Know Anthropic’s business is growing quickly, with launch‑driven step‑changes that mean what worked last quarter may not generalize. Methodology direction is a research program, not a settled architecture. You’ll be building practices and systems while also delivering a monthly number, alongside an Analytics Engineer who is building the platform underneath you.
Annual Salary $270,000—$320,000 USD
Logistics
Minimum education:
Bachelor’s degree or an equivalent combination of education, training, and/or experience.
Required field of study:
A field relevant to the role as demonstrated through coursework, training, or professional experience.
Minimum years of experience:
Years of experience required will correlate with the internal job level requirements for the position.
Location‑based hybrid policy:
We expect all staff to be in one of our offices at least 25% of the time; some roles may require more time in our offices.
Visa sponsorship:
We do sponsor visas. However, we aren’t able to successfully sponsor visas for every role and every candidate. If we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.
Candidate Safety To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies that identify themselves as working on behalf of Anthropic. Legitimate recruiters will never ask for money, fees, or banking information before your first day. If you’re ever unsure about a communication, don’t click any links—visit anthropic.com/careers directly for confirmed position openings.
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Sprachkenntnisse
- English
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