Data-Driven Supply Strategy Analyst – Canada Middle Mile

Amazon; Tempe (AZ); On-site; USD 34,000 - 45,000; Full time

Benefits offered by this job

Health insurance

401(k) matching

Paid time off

Parental leave

Job summary

Amazon's Carrier Services team is seeking a Supply Strategy Analyst to support data-driven decisions for the Canada middle mile transportation network. This role will pull and analyze supply program data, support load distribution reporting across 3P carrier programs and RLB/RFA auction and Day Rate supply types, and prepare analyses that balance cost efficiency with network capacity.

The ideal candidate is comfortable with large datasets, proficient in SQL and Excel, and able to turn data into

Qualifications

• High school or equivalent diploma.
• Intermediate Excel skills (pivot tables, charts, lookups, nested IFs).
• Experience handling large data sets and using data to drive improvements.

Responsibilities

• Pull and consolidate supply program data across Day Rate, Relay Freight Auction, and Relay Load Board to support planning cycles.
• Prepare and maintain Weekly Business Review reporting and the Canada Supply Flash, including variance summaries and trend analysis.
• Support documentation and standardization of Canada supply planning processes, including POR tracking and HVE planning cycles.
• Track weekly volume forecasts and flag variances to the planning team.
• Coordinate data collection across Finance, CTS, and Supply Planning teams to meet deadlines.
• Respond to ad hoc data and reporting requests from team leads and stakeholders.

Skills

SQL

Excel

Data analysis

Data management

Education

Bachelor's degree

High school diploma

Job description

Amazon's Carrier Services team is seeking a Supply Strategy Analyst to support data-driven decisions for the Canada middle mile transportation network. This role will pull and analyze supply program data, support load distribution reporting across 3P carrier programs and RLB/RFA auction and Day Rate supply types, and prepare analyses that balance cost efficiency with network capacity.

The ideal candidate is comfortable with large datasets, proficient in SQL and Excel, and able to turn data into