Staff Data Scientist (Forecasting)
Posted Updated
Description
- 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
- A track record of delivering adjustable, well‑calibrated, and explainable forecasting systems that informing decision-making
- Strong SQL skills (Hive/Presto/Spark SQL) and experience building reliable data pipelines/workflows (e.g., Airflow)
- Strong background in time‑series modeling and applied statistics/econometrics; advanced degree (MS or PhD) preferred
- 8+ years of combined post-graduate academic and industry experience building and shipping production time‑series/forecasting models with web‑scale data
- Business acumen and ownership mindset—able to simplify complex problems, connect model outputs to business levers, and prioritize for impact
- Proven technical leadership—success leading critical projects and materially influencing the scope and output of other contributors
- Expertise in at least one scripting language (ideally Python)
- Excellent communication skills—able to distill complex analyses and uncertainty into concise narratives for executive audiences