Senior Manager, Analytics & AI

Role Overview

• Build and scale enterprise AI and machine learning capabilities across supply chain functions including logistics, distribution, planning, sourcing, and labor.
• Translate business problems into well-defined AI use cases, with clear success metrics and operational outcomes.
• Define and operationalize standard frameworks for AI use-case intake, prioritization, development, deployment, and lifecycle management.
• Lead the end-to-end delivery of ML-driven solutions, from problem framing and model development through production deployment and adoption tracking.
• Own and continuously evolve the Supply Chain Data Science & AI roadmap, aligned with business priorities, AOP commitments, and long-term capability goals.
• Partner with data engineering, BI, and IT teams to embed AI solutions into dashboards, workflows, and operating processes, not standalone models.
• Lead AI solution design using Microsoft technologies, including Azure AI, Azure Foundry, Copilot, and Power Platform.
• Drive adoption of GenAI, copilots, and AI agents in a secure, scalable, and governed manner.
• Evaluate, pilot, and integrate external AI tools and vendors, ensuring fit with enterprise data architecture, security standards, and long-term scalability.
• Establish best practices for model development, deployment, monitoring, explainability, and reuse, enabling repeatable delivery.
• Mentor and develop analysts and data scientists, raising overall AI maturity and execution rigor across the organization.
• Communicate progress, risks, and outcomes to senior stakeholders using clear, business-focused language.

Requirements

• Bachelor’s or Master’s degree in Data Science, Computer Science, Engineering, Supply Chain, or a related field.
• 8+ years of experience in data science, machine learning, or advanced analytics roles.
• Proven experience deploying machine learning solutions in production environments, not just proofs of concept.
• Strong programming skills in Python and proficiency in SQL.
• Experience working with large-scale data, modern ML frameworks, and enterprise analytics platforms.
• Demonstrated application of analytics in supply chain, logistics, operations, or planning domains.
• Strong understanding of the AI/ML lifecycle, including deployment, monitoring, governance, and ongoing optimization.
• Ability to translate complex technical concepts into clear business outcomes and influence cross-functional stakeholders.
• Experience leading complex initiatives in a global, matrixed enterprise environment.

Tech Stack

• Azure
• Python
• SQL

Benefits

• Health insurance
• Retirement plans
• Paid time off
• Flexible work arrangements
• Professional development