The Senior Manager, Enterprise Logistics Analytics & Optimization will lead the design, execution, and sustainment of enterprise logistics analytics capabilities across the network. This role owns advanced data modeling, cost-to-serve analytics, and network optimization initiatives that enable commercial monetization and operational performance improvement.
This position serves as the technical and commercial analytics lead within Enterprise Logistics, translating complex modeling outputs into executive-level insights and shaping program strategy.
What You Will Do in this Role:
Enterprise Logistics Program Leadership:
- Lead analytics workstreams across enterprise logistics initiatives
- Own development and governance of cost-to-serve and monetization models
- Support CSA renegotiation strategy with data-driven financial modeling
- Translate analytics into executive-ready materials for senior leadership
Advanced Analytics and Optimization Ownership:
- Architect and maintain enterprise-level data models
- Lead SQL and Python-based analytics solutions
- Design and oversee optimization scenarios including network design and capacity modeling
- Serve as internal subject matter expert for network modeling tools such as Optilogic.
- Commercial and Financial Integration
- Partner with Finance to validate revenue and margin impact
- Develop financial sensitivity models and scenario analysis
- Quantify value realization and track performance against targets
- Capability Sustainment and Governance
- Establish modeling standards, documentation, and version control
- Build and institutionalize repeatable analytics frameworks
- Mentor and develop analysts
- Support long-term sustainment of installed capabilities
What Qualifications You Will Need:
Experience and Education
- 6–10+ years in supply chain analytics, operations research, consulting, or transformation roles
- Experience leading modeling or optimization programs - Required
- Bachelor’s degree in Engineering, Operations Research, Supply Chain, Data Science, or related quantitative field required
- Master’s in Industrial Engineering, Operations Research, Analytics, or related technical discipline preferred
Required Competencies
- Advanced SQL and strong Python proficiency - Required
- Deep understanding of optimization and modeling concepts - Required
- Strong financial acumen and cost-to-serve modeling capability - Required
- Executive communication and presentation skills – Required
- Ability to lead cross-functional initiatives - Required
- Systems thinking across ERP and supply chain environments - Required
