# Data Scientist, Finance Forecasting

**Company:** [Anthropic](https://hotfix.jobs/companies/anthropic)
**Location:** San Francisco, CA
**Role:** Data Science
**Salary:** $265k – $320k/yr
**Skills:** Python, SQL, Forecasting, time series, Causal Inference, prophet, ets, arima, gradient boosting, neural forecasting, hierarchical reconciliation, backtesting, bayesian structural time series, timegpt
**Posted:** 2026-08-05

> Builds and owns production revenue forecasting and causal measurement models for Finance, establishing rigorous backtesting, accuracy tracking, and executive-ready recommendations. Requires strong Python, SQL, applied statistics, and experience deploying models in production.

## Job Description

## Responsibilities

- Own a core part of the modeling work, including production revenue forecasts or causal measurement for launches and events.
- Develop, deploy, monitor, backtest, and improve production models.
- Build accuracy tracking and establish a cross-methodology accuracy baseline as a standing Finance metric.
- Research event-aware forecast architectures, hierarchical reconciliation, and causal designs for launch-driven changes.
- Translate model outputs and accuracy results into recommendations for Finance and executive leadership.
- Partner with the Analytics Engineer on feature pipelines, model deployment, and the forecast store.

## Requirements

- Substantial experience in data science, forecasting, or quantitative finance, including ownership of production models.
- Deep fluency in Python and SQL and experience productionizing analytical work.
- Strong applied statistics foundation, with depth in either production time-series methods or causal inference.
- Experience with backtesting and accuracy tracking.
- Experience presenting and defending forecasts or causal estimates to executives.
- Bias for action and comfort working in ambiguous, early-stage environments.
- Bachelor's degree or equivalent combination of education, training, and experience in a relevant field.

## Preferred Qualifications

- Experience with exogenous-regressor or event-aware forecasting.
- Familiarity with hybrid or foundation-model forecasting systems such as TimeGPT-class systems.
- Background in pricing and elasticity modeling or marketing-mix modeling.
- Experience forecasting consumption-based or usage-billed businesses.

## Compensation and Benefits

- Annual salary range: **$265,000–$320,000 USD**.
- Competitive compensation and benefits.
- Optional equity donation matching.
- Generous vacation and parental leave.
- Flexible working hours.
- Office space for collaboration.

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