Lead the strategy, development, and implementation of forecasting models, and code for critical systems. This role requires overlap with the US PDT time zone on a daily basis.
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.
Architect, develop, and deploy scalable forecasting and Machine Learning (ML) solutions using Python, and drive the adoption of coding practices to ensure repeatable analyses that optimize global vendor operations.
Minimum qualifications:
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.
Preferred qualifications:
5 years of experience in a data-driven environment, building and deploying investigative solutions at scale.
Ability to write SQL and use Python to build data pipelines, analyze data, and develop forecasting models (statistical or ML).
Ability to influence executive stakeholders and manage projects with minimal oversight.
Ability to work flexible hours aligned with North America.
