Transportation Scheduler & Analytics Lead

Amazon

Tempe (AZ)

On-site

USD 41,000 - 67,000

Full time

4 days ago
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Job summary

Amazon’s Network Engineering & Scheduling Technology (NEST) team in Tempe seeks an experienced Transportation Specialist to own load scheduling and develop end-to-end transportation processes. You will pull data, create ad hoc reports, and drive performance metrics to support growing business segments.

The role requires strong data skills, the ability to interpret trends, and effective communication to present weekly findings and variances to goals.

Qualifications

  • 1+ years of experience with computers and Microsoft Office (Outlook, Word, and Excel).
  • High school or equivalent diploma.
  • Fluent in English (read, write, and speak).
  • Ability to lift up to 49 pounds, stand/walk for up to 12 hours, and push/pull/squat/bend/reach.
  • Work 40 hours/week, and overtime as required.
  • Flexible schedule including weekends, nights, and/or holidays.
  • 18 years of age or older.

Responsibilities

  • Pull data from multiple databases using Excel, Access, SQL, or similar tools and perform ad hoc reporting.
  • Develop and understand performance metrics to drive business results.
  • Understand the business impact of trends and make data-driven decisions.
  • Elevate data issues to owners and ensure timely resolutions.
  • Work within tight timeframes to meet critical business needs while tracking activities.
  • Communicate findings clearly, verbally and in writing, in review forums.
  • Collaborate across teams to support transportation scheduling processes.

Skills

Microsoft Office
Data analysis
English fluency

Education

High school diploma

Tools

Excel
Access
SQL

Job description

Amazon’s Network Engineering & Scheduling Technology (NEST) team in Tempe seeks an experienced Transportation Specialist to own load scheduling and develop end-to-end transportation processes. You will pull data, create ad hoc reports, and drive performance metrics to support growing business segments.

The role requires strong data skills, the ability to interpret trends, and effective communication to present weekly findings and variances to goals.

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