Forecasting Leader — Global Customer Service & Analytics

Amazon Inc.; Seattle (WA); On-site; USD 115,000 - 160,000; Full time

Job summary

Amazon is seeking a Sr. Forecasting Manager for the Network Solutions Forecasting team within Amazon Customer Service.

The role focuses on end-to-end workforce planning, forecasting models, and real-time management to support global customer service operations. The ideal candidate blends advanced mathematics or statistics with actionable business recommendations, capable of explaining forecast variance and persuading senior leaders.

Qualifications

• Bachelor's degree in supply chain, business, engineering, finance or related technical/quantitative field.
• 5+ years of experience as a forecasting analyst or related positions.
• Experience with SQL and one or more of the statistical modeling languages/toolboxes like R or Python.
• Excellent communication skills (verbal and written) to share findings with executives.
• Ability to work successfully in a dynamic, fast-paced environment.

Responsibilities

• Model forecasting problems, discover insights and identify opportunities using statistical, machine learning, algorithmic, data mining and visualization techniques.
• Collaborate with stakeholders to analyze forecast variances, identify variance drivers and improve operational efficiencies.
• Apply diverse tools and data sources to answer high-impact business questions and present concise insights.
• Communicate insights to non-technical audiences and drive issues to resolution.

Skills

Forecasting analytics

Statistical modeling

Communication

Time-series

Cross-functional collaboration

Education

Bachelor's degree in supply chain, business, engineering, finance or related field

MBA or related Master’s degree (preferred)

Tools

SQL

Python/R

Job description

Amazon is seeking a Sr. Forecasting Manager for the Network Solutions Forecasting team within Amazon Customer Service.

The role focuses on end-to-end workforce planning, forecasting models, and real-time management to support global customer service operations. The ideal candidate blends advanced mathematics or statistics with actionable business recommendations, capable of explaining forecast variance and persuading senior leaders.