The Sr. Manager, Logistics Analytics & Optimization will support data-driven decision-making and operational optimization across the Distribution Center and Contact Center network. Reporting to the Director, Logistics Analytics and Optimization, this role involves developing and implementing analytical models, algorithms, tools, and automated processes to improve network performance, productivity, capacity, service, and cost. The successful candidate will analyze supply chain data to identify trends and root causes, translating complex data into actionable insights for functional leaders. Key responsibilities include deploying machine learning algorithms in production environments and leveraging AI, automation, forecasting, and advanced analytics to simplify work. Candidates must possess a quantitative degree and experience in operations research or supply chain analytics, utilizing skills in scaling and monitoring machine learning models to solve complex logistics and operational problems.
Develop and implement analytical models, algorithms, and automated processes to improve operational performance.
Analyze supply chain data to identify trends, root causes, and opportunities for productivity and cost improvements.
Translate complex data into clear, actionable insights and recommendations for functional leaders.
Partner with cross-functional teams to develop and implement scalable analytical and optimization solutions.
Leverage AI, machine learning, and forecasting to simplify work and optimize network performance.
Measure the business impact of analytical solutions and recommend enhancements for continuous improvement.
Deploy machine learning algorithms into production environments.
What we're looking for
Degree in Computer Science, Data Science, Engineering, Mathematics, Statistics, or a related quantitative field.
9+ years of experience in advanced analytics, data science, operations research, supply chain analytics, or a related field.
Experience in deploying, scaling, and monitoring machine learning models.
Experience applying AI and machine learning capabilities to identify opportunities, improve decision-making, automate processes, and optimize operational performance.
Ability to work at a detailed level while summarizing findings to make strong recommendations for change.
Ability to collaborate with cross-functional teams and influence product and analytics roadmaps.
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