Lead the strategy, development, and implementation of complex forecasting models, and Google-standard code for critical systems.

Own the functional requirements and data pipelines for critical operational metrics, either directly or through oversight of supplier resources.

Act as a technical mentor for statistical methods and other investigative solutions and provide technical oversight to unblock automation goals.

Drive problem framing for ambiguous and complex programs, build new processes with the foresight to address future business challenges.

Architect, develop, and deploy scalable forecasting and Machine Learning (ML) solutions using Python, and drive the adoption of Google-standard coding practices to ensure robust, repeatable analyses that optimize global vendor operations.

Master's degree in a quantitative discipline such as Statistics, Engineering, Sciences, or equivalent practical experience.

4 years of experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis.