Staff Data Scientist, Forecasting

Responsibilities

• Be the technical lead for the forecasting team.
• Own the strategy and implementation of forecasting models of key company metrics (e.g., monthly active users), delivering accurate, interpretable forecasts at scale.
• Lead the full modeling lifecycle end to end: problem framing, feature engineering, model development and prototyping, experimentation and backtesting, deployment, monitoring/drift detection, and explainability.
• Set the forecasting technical vision. Define model architectures and standards, and partner with Engineering to shape the forecasting platform for efficient training/inference today and the scalability needed for the next generation of models.
• Translate forecasts into decisions. Present outputs, scenario analyses, and recommendation frameworks to senior leadership with clarity and brevity. This is a high‐visibility role with regular VP-level exposure.
• Drive broader time‐series impact beyond point forecasts—e.g., anomaly detection, automated root‐cause analysis, campaign/channel attribution, and early‐warning signals for business health.
• Embed forecasting into the business.
• Partner with BizOps/Finance and product teams to integrate forecasts and insights into operational rhythms, executive decision-making, and strategic planning.
• Lead and mentor. Guide the work of at least two data scientists, raising the bar on technical quality, execution, and impact through candid, continuous feedback and coaching.

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