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ML
Matson Logistics, Inc
AI Specialist - Matson Logistics
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What they do
A Logistics Specialist plans and manages logistics, including the distribution and transportation of supplies, equipment or materials for a company or organization. Develops order schedules and policies, tracks shipments, coordinates storage and works with suppliers and transportation companies. Implements efficient and cost-effective transportation and distribution systems.
$64,820 / year median in Illinois
-5% projected decline
Job Description
AI Specialist - Matson Logistics Matson Logistics, Inc - 3.8 Downers Grove, IL Job Details Full-time $120,000 - $145,000 a year 20 hours ago Benefits Profit sharing Paid holidays Disability insurance Health insurance Dental insurance Paid time off Adoption assistance Vision insurance 401(k) matching Life insurance Qualifications AI models Optimizing workflow processes Project team coordination Systems integration Data Integration (Data management) Tooling Data preparation projects Enterprise software Generative models Process improvement AI platforms (beyond public GPTs) Integration Platforms (Enterprise solutions) Prototype creation AI-driven automation Prototypes Stakeholder relationship building Generative AI Full Job Description About Us Matson Logistics is a leading provider of multimodal transportation, warehousing, and distribution services throughout North America. Known for our innovative solutions and financial strength and stability, Matson Logistics' people, processes, and systems work together to deliver superior performance and value to our customers every day. Click here to learn more about us! About the Role We are looking for a hands-on AI Specialist to build and support AI solutions on the business side of Matson Logistics (ML). This position is ML's dedicated spoke-level AI/data resource in the enterprise hub-and-spoke model. It partners closely with Matson's IT and AI Acceleration teams (Hub), while owning execution and adoption across ML's four lines of business (LOBs). Because the work touches every line of business, this position reports to ML's Manager, Strategic Planning and Operational Excellence rather than to a single line of business (LOB). Where there is a clear business owner for a solution, the person in this role builds it alongside them, sitting together to build and deploy it so that owner comes away understanding how it runs. Other times there is no one to build with, and they build and deploy the solution directly. Either way, they stay involved after launch, stepping in to fix workflows and agents when they break. This role operates with clear boundaries between business-led solution development and enterprise platform ownership. It is responsible for business-side solution design, build, and adoption, while IT retains ownership of platform integrity, security, architecture, and enterprise integrations. When a problem is outside what they can fix, such as a platform, environment, security, or integration issue, it goes to IT. The role will change as we go. As the build backlog matures, the role's mix shifts toward optimization, scaling proven solutions across LOBs, turning large unstructured data into actionable business insights, and Power BI or other business intelligence reporting. Because the AI space moves quickly, we need someone who is comfortable working without a fixed playbook and can adjust as priorities and tools change. Top 3 Accountabilities Build and deploy business-side AI solutions across the Matson Logistics lines of business using Microsoft tools (Copilot Studio, Power Automate, Power Apps), starting with quick wins and moving toward the more involved builds over time. Keep deployed solutions running by monitoring performance, fixing workflows and agents within the business layer, and escalating platform, security, data, or integration issues to IT through established escalation paths. Grow adoption and give the governance board a weekly update on where things stand, what is broken, what is being fixed, and the business value being delivered. What you'll do: Work with teams across the lines of business to learn their workflows, surface AI opportunities, and gather requirements for new use cases. Build and deploy AI solutions with Microsoft tools such as Copilot Studio, Power Automate, and Power Apps, covering needs that sit outside IT's enterprise roadmap. Coach and coordinate with ML's network of nominated Copilot Studio power users across LOBs, multiplying delivery capacity beyond this single role. Operate within defined enterprise standards for platform use, security, and governance, while independently managing business-side delivery within those guardrails. Support deployed solutions beyond the light day-to-day upkeep the business owner handles, diagnosing and fixing broken workflows and agents when they need more than the requester can manage. Handle business data responsibly and follow security, privacy, and compliance standards with IT, especially for solutions that touch Finance and HR data. Set and sequence priorities with the Strategic Planning and Operational Excellence Manager, contributing input and starting with high-value quick wins before taking on larger builds. Track adoption, usage, and results, and keep dashboards and performance metrics current. Report weekly to the governance board and prepare updates and recommendations for leadership and business partners. Act as the connection point between the business teams and the technology teams. Key Interfaces Brokerage, MLSC, MLW, and Span Alaska lines of business IT / Innovation Finance Governance board (a cross-functional board that oversees AI initiatives and priorities and keeps the effort on track) Business users who request and use the solutions day to day You have these skills: Practical, disciplined approach to AI adoption. Builds solutions with people, not just for them. Takes ownership of solutions after launch, not only at delivery. Collaborates well across business and IT teams. Comfortable navigating and structuring unstructured data to enable practical AI use cases. Focused on results rather than experimentation for its own sake. Strong communication and facilitation. Curious about systems, data workflows, automation, and analytics. Builds trust and aligns stakeholders without relying on direct authority.