Build and maintain station-level capacity models for all Peak events, working with forecasting, operations, and network teams
Identify capacity gaps (mechanical, OTR, UTR) early and drive resolution through established levers (DILO changes, route additions, overlap jurisdiction, CPT
shifts)
Create and run the governance mechanisms (WBRs, readiness reviews, escalation paths) that ensure the network hits readiness milestones on schedule
Partner with Operations, Last Mile, Middle Mile, and Tech teams to align inputs and commitments
Produce clear, data-driven recommendations for senior leadership when trade-offs are required
Build post-event retrospectives that feed learnings back into the next planning cycle
Bachelor's degree or above in Supply Chain Management, Engineering, Math, Business or other related quantitative disciplines
Experience in similar technical or vocational roles
Experience with advanced use of Excel and using statistical analysis applications, or experience with Microsoft Office including Outlook, Word, and Excel
Experience in building financial and operational reports/data sets that inform business decision-making, or experience with data analytics platforms (Power BI, Python, SQL, Tableau)
Experience in communicating technical concepts to a non-technical audience
Experience communicating with a wide range of stakeholders, including colleagues and leadership, or experience in an operational role
Experience identifying and resolving complex issues
Speak, write, and read fluently in English, and have the ability to take direction in English
Experience in program management, logistics, operations, supply chain, transportation, or a related field
Knowledge of capacity planning concepts
Knowledge of BI analytics, reporting or visualization tools like Tableau, AWS QuickSight, Cognos or other third-party tools
Experience in accounts receivable or account payable, or experience participating in continuous improvement projects in your team to scale and improve controllership with measurable results
Experience in creating process improvements with automation and analysis, or experience working with Excel and large-scale data mining and reporting tools such as Python, SQL, or Tableau
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