Staff Data Scientist, Forecasting

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Company Overview

A global technology platform is focused on helping millions of people discover creative ideas, explore new possibilities, and plan meaningful experiences. The organization combines technology, creativity, data, and artificial intelligence to build products that inspire users around the world.

The organization is also advancing the use of AI as a collaborative technology that augments creativity and increases business impact. Employees are encouraged to embrace innovation, explain their approaches clearly, and apply both foundational technical expertise and AI capabilities to solve complex problems.

The Staff Data Scientist, Forecasting will serve as the technical lead for the forecasting team, owning the strategy and implementation of forecasting models for key company metrics. The role will deliver accurate, interpretable forecasts at scale while influencing technical direction, business decisions, and the next generation of forecasting capabilities.

Key Responsibilities

• Serve as the technical lead for the forecasting team.
• Own the strategy and implementation of forecasting models for key company metrics, including monthly active users.
• Develop accurate, interpretable, and scalable forecasting systems.
• Lead the complete modeling lifecycle, including problem framing, feature engineering, model development, prototyping, experimentation, backtesting, deployment, monitoring, drift detection, and explainability.
• Establish the technical vision, model architectures, and standards for forecasting.
• Partner with Engineering teams to shape forecasting infrastructure for efficient model training and inference.
• Help develop scalable forecasting platforms capable of supporting future generations of models.
• Translate forecasts, scenario analyses, and recommendations into concise insights for senior leadership.
• Present forecasting outputs and strategic recommendations to senior executives, including VP-level stakeholders.
• Expand the use of time-series analytics beyond point forecasts through anomaly detection, automated root-cause analysis, campaign and channel attribution, and early-warning signals for business health.
• Partner with Business Operations, Finance, and Product teams to integrate forecasts and insights into operational processes, executive decision-making, and strategic planning.
• Lead and mentor at least two data scientists, providing continuous feedback and coaching while raising standards for technical quality, execution, and business impact.
• Drive broader organizational impact by connecting forecasting capabilities to important business decisions and strategic priorities.

Required Qualifications

• 8+ years of combined postgraduate academic and industry experience building and deploying production time-series or forecasting models using large-scale data.
• Proven experience delivering adjustable, well-calibrated, and explainable forecasting systems that support business decision-making.
• Strong background in time-series modeling and applied statistics or econometrics.
• Advanced degree such as a Master’s or PhD is preferred.
• Expertise in at least one scripting language, preferably Python.
• Strong SQL skills, including experience with technologies such as Hive, Presto, or Spark SQL.
• Experience building reliable data pipelines and workflows using tools such as Airflow.
• Strong business acumen and an ownership mindset, with the ability to simplify complex problems and connect model outputs to business opportunities.
• Ability to prioritize technical work based on business impact.
• Excellent communication skills, with the ability to communicate complex analyses, forecasts, and uncertainty clearly to executive audiences.
• Proven technical leadership experience, including leading critical projects and influencing the work and output of other contributors.
• Strong collaboration skills and the ability to work effectively with technical and business stakeholders.

Working Model

• The position is based in San Francisco or can be performed remotely.
• The role requires in-person collaboration approximately 1–2 times per quarter.
• The position can therefore be situated anywhere within the country.
• The position is not eligible for relocation assistance.
• The working model is designed to balance flexibility with opportunities for meaningful collaboration and connection.

Disclaimer

SpringCube curates tech job listings from various company websites to support tech professionals globally.

1. No Endorsement: Job ads on SpringCube do not imply endorsement of their authenticity or quality.
2. No Client Relationship: This company is not a client of SpringCube unless stated.
3. To Apply: Click the Apply button to be redirected to the hiring company’s application page for this job.
4. No Liability: SpringCube is not liable for inaccuracies.