Pinterest is hiring a remote Staff Data Scientist Forecasting!
Pinterest is hiring a Staff Data Scientist to serve as technical lead for its forecasting team, owning both the strategy and hands-on execution of models that predict core company metrics such as monthly active users. This is a high-visibility, individual-contributor leadership role with regular VP-level exposure, where the successful candidate will not only build accurate, interpretable forecasts at web scale but also translate them into scenario analyses and recommendation frameworks that shape executive decision-making and strategic planning. Beyond point forecasts, the team's mandate spans anomaly detection, automated root-cause analysis, channel and campaign attribution, and early-warning signals for business health. The role also carries a formal mentoring component, guiding at least two data scientists and raising the technical bar through candid, continuous feedback. Pinterest positions the role as remote-friendly — candidates can be based anywhere in the country — while expecting in-person collaboration roughly one to two times per quarter. The company emphasizes AI as an embedded partner in its work and hiring process, and expects candidates to articulate their reasoning clearly, not just their results. Compensation is transparent and includes equity in addition to base salary.
Key responsibilities
- Set the technical vision and standards for forecasting model architectures, and own the strategy and implementation behind key company metric forecasts
- Lead the full modeling lifecycle end to end: problem framing, feature engineering, prototyping, experimentation and backtesting, deployment, drift monitoring, and explainability
- Partner with Engineering to evolve the forecasting platform for efficient training and inference today and for next-generation model scalability
- Present forecasts, scenario analyses, and recommendation frameworks to senior leadership with clarity and brevity
- Extend time-series impact beyond point forecasts into anomaly detection, automated root-cause analysis, campaign and channel attribution, and business health early-warning signals
- Partner with BizOps/Finance and product teams to embed forecasts into operational rhythms, executive decision-making, and strategic planning
- Mentor at least two data scientists, elevating technical quality, execution, and impact through continuous coaching and feedback
Key requirements
- 8+ years of combined post-graduate and industry experience building and shipping production time-series and forecasting models on web-scale data
- Demonstrated track record of delivering adjustable, well-calibrated, explainable forecasting systems that inform decisions
- Strong grounding in time-series modeling and applied statistics or econometrics; MS or PhD preferred
- Expertise in at least one scripting language, ideally Python
- Strong SQL skills across Hive, Presto, or Spark SQL, plus experience building reliable data pipelines and workflows such as Airflow
- Business acumen and an ownership mindset: able to simplify complex problems, connect model outputs to business levers, and prioritize for impact
- Excellent communication skills, including the ability to distill complex analyses and uncertainty into concise executive narratives
- Proven technical leadership, having led critical projects and materially influenced the scope and output of other contributors
- Seniority: Staff (8+ years experience)
- Work mode: Remote anywhere in the country; in-office 1-2 times per quarter for collaboration
- Salary: $164,695 - $339,078 USD base, plus equity
- Key skills: Time-series forecasting, Applied statistics, Econometrics, Python, SQL (Hive/Presto/Spark SQL), Airflow, Data pipelines, Model deployment and monitoring, Experiment design and backtesting, Anomaly detection, Attribution modeling, Technical leadership, Mentoring, Executive communication
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