Data Scientist (Finance Forecasting)

TL;DR

Data Scientist (Finance Forecasting): Building and optimizing revenue forecasting models and causal measurement programs to drive capacity planning and financial reporting with an accent on time-series forecasting and causal inference. Focus on developing production-ready models, establishing backtesting disciplines, and translating quantitative results into executive recommendations.

Location: San Francisco, CA. Hybrid: Must be in office at least 25% of the time.

Salary: $265,000 - $320,000 USD

Company

AI research lab dedicated to creating reliable, interpretable, and steerable AI systems for the benefit of society.

What you will do

• Own production revenue forecasts, including scoping, development, backtesting, deployment, and monitoring.
• Lead the causal measurement program to analyze how launches and specific events move revenue.
• Establish a cross-methodology accuracy baseline and backtesting discipline as a standing Finance metric.
• Contribute to research on event-aware forecast architectures and hierarchical reconciliation.
• Partner with Analytics Engineers on feature pipelines and model deployment.
• Present and defend model outputs and recommendations to executive leadership.

Requirements

• Substantial experience in data science, forecasting, or quantitative finance with a track record of owning models in production.
• Deep fluency in Python and SQL.
• Strong foundation in applied statistics, with depth in either production time-series methods or causal inference.
• Experience building backtesting and accuracy-tracking disciplines.
• Proven ability to present quantitative results to executives.
• Bachelor’s degree or equivalent combination of education and professional experience.

Nice to have

• Experience with exogenous-regressor or event-aware forecasting approaches.
• Familiarity with foundation-model forecasting (e.g., TimeGPT).
• Background in pricing, elasticity modeling, or marketing-mix modeling.
• Experience forecasting consumption-based or usage-billed business models.

Culture & Benefits

• Competitive compensation and optional equity donation matching.
• Generous vacation and parental leave.
• Flexible working hours and collaborative office space in San Francisco.
• Environment focused on "big science" and long-term AI safety impact.
• Visa sponsorship availability.