Why This Role Stands Out
This role offers a fantastic opportunity to shape the future of AI in logistics, driving impactful innovation within a reputable company. You'll thrive here if you possess a strong blend of AI/ML expertise, data analytics skills, and a passion for transforming operations through technology, making it an ideal next step for your career growth.
Quick Overview
Job Description
Century Distribution Systems seeks an AI Enablement Lead to drive adoption of AI and advanced analytics across global logistics operations. You will partner with product, IT, and operations teams to identify high impact use cases in transportation and warehousing, design solutions using data, ML, and automation, and guide pilots through to scaled deployment. Responsibilities include roadmap ownership, vendor and tool evaluation, data readiness coordination, change management, training, and value tracking. You'll champion innovation, align initiatives with customer and business goals, and help build a culture of data-driven continuous improvement.
Responsibilities
- Lead AI enablement strategy for transportation and warehousing operations
- Identify and prioritize high value AI and analytics use cases with business stakeholders
- Translate logistics challenges into actionable data and ML solution requirements
- Coordinate data readiness, integration, and tooling with IT and data teams
- Evaluate and select AI platforms, tools, and external vendors as needed
- Manage pilots, measure impact, and drive successful scale up of AI solutions
- Develop training and change management plans to increase adoption
- Create and maintain an AI roadmap aligned to customer and business goals
- Establish success metrics and track value realization across initiatives
- Promote a culture of data driven, continuous improvement across global teams
Required Skills
- AI/ML concepts and lifecycle management
- Data analytics and data modeling
- SQL and data querying
- Cloud analytics platforms (AWS, Azure, or GCP)
- Python or similar language for data/ML workflows
- Business intelligence and dashboarding tools
- Product or project management
- Change management and stakeholder communication
- Knowledge of transportation and warehousing operations
- Requirements gathering and documentation
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