CI Special Project Manager

Daimler Truck North America•Fort Mill, SC

1d•Hybrid

About The Position

Inside the Role We are looking for a highly structured, analytical, and collaborative individual who will lead strategic end to end initiatives focused on continuous improvement across operations and supply chain. This individual will connect people, processes, and systems across the network to elevate operational performance and drive sustainable efficiencies. The ideal candidate for this role will apply strong operational excellence expertise—particularly in Lean Manufacturing, Lean Logistics and Supply Chain, —to support the execution of cross-functional initiatives and ensure the organization is operationally ready for future business needs. This role will be dedicated full time to a various CI project across the organization. The first project this role will lead is Come Together. This project aims to connect people, processes, and systems across DTNA’s end-to-end supply chain — with a focus on reducing costs, improving cash flow, and implementing an E2E supply chain management system. During this project the role will be a member of the Transportation team under Alicia Hogan. Posting Information We provide a scheduled posting end date to assist our candidates with their application planning. While this date reflects our latest plans, it is subject to change, and postings may be extended or removed earlier than expected. We Take Care of Our Team What You Drive at DTNA

Requirements

Bachelor’s Degree in Supply Chain Management, Industrial/Manufacturing Engineering, Business, Operations Management, or a related field.
10+ years of experience in Supply Chain, Operations, Operational Excellence, Logistics, or related disciplines preferred
Strong knowledge and practical application of Lean Manufacturing and Lean Logistics principles.
Proven ability to connect complex end to end topics and translate them into actionable insights.
High‑level project management capabilities with experience leading cross-functional initiatives.
Strong analytical, strategic-thinking, and structured problem‑solving skills.
Experience supporting Operational Readiness efforts for new processes, products, or systems.
Excellent verbal and written communication skills.
Proficient in Microsoft Office Suite (Excel, PowerPoint, Word).
Ability to manage confidential information appropriately.
Availability to travel as required.

Nice To Haves

Professional Lean certifications or logistics-focused credentials

Responsibilities

Lead strategic initiatives focused on reducing costs and improving end to end processes across Operations
Connect processes, data flows, and system interactions to identify gaps, dependencies, and improvement opportunities.
Apply Lean Manufacturing and Lean Logistics principles to optimize material flow, transportation efficiency, and inventory management.
Facilitate cross-functional collaboration between Operations, In-plant Logistics, Supplier Management Material procurement, Manufacturing Engineering, and Finance among others.
Conduct stakeholder analysis and create engagement plans to ensure alignment, transparency, and successful project execution.
Lead Operational Readiness activities to support major launches, process changes, and system integrations.
Drive continuous improvement across various operational processes and support the deployment of operational excellence frameworks.
Apply strong project management skills to plan, track, and deliver complex initiatives on time.
Prepare and present clear, concise analyses, executive presentations, and recommendations to senior leadership.
Support the development and standardization of KPIs and reporting tools.
Monitor performance, identify root causes of gaps, and drive corrective actions in partnership with plant and logistics teams.
Ensure alignment with broader DTNA operational strategies
Evaluate process inefficiencies that could be mitigated through automation, algorithmic optimization, or AI‑supported scenario modeling.
Leverage AI‑supported forecasting, root‑cause analysis, and predictive modeling to improve supply chain accuracy, reliability, and responsiveness.