Data Scientist, Finance Forecasting

The shape of it

In the posting’s own words

As an early member of our Finance Analytics and Business Intelligence team, you will play an instrumental role in our company's mission of building safe and beneficial artificial intelligence by establishing robust analytics engineering and business intelligence capabilities for our Finance & Accounting organization. In this unique company, technology, and moment in history, your work will be critical to ensuring accurate financial reporting, streamlining accounting processes, and supporting our financial operations as we deploy safe, frontier AI at scale to the world.

What it asks for · 6

• 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 (Prophet, ETS, ARIMA, gradient-boosted approaches, neural forecasting, hierarchical reconciliation) or causal inference (difference-in-differences, synthetic control, Bayesian structural time series, event studies)
• 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

Also a plus

• 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 the job covers

• Own a core piece of the team's modeling work — either the production revenue forecasts themselves (scoping, development, backtesting, deployment, monitoring) 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

Tools and skills named

Words the posting leans on

• forecasting14×
• models12×
• causal10×
• forecast10×
• backtesting7×
• finance7×
• production7×
• build6×
• experience6×
• modeling6×
• accuracy5×
• event5×
• analytics4×
• approaches4×
• business4×
• comfortable4×

Counted from the posting after the mission statement and the legal notices are set aside. The ones near the top are the ones a screener is looking for.

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