Sr. Manager, Logistics Analytics &… at Reality Gap · Centervil…

Sr. Manager, Logistics Analytics & Optimization

Location: OFC Ohio Fulfillment Center · Not Remote

About the Role

In this position you will support the advancement of data-driven decision-making and operational optimization across Gap Inc.’s Distribution Center and Contact Center network. Reporting to the Director, Logistics Analytics and Optimization, this role translates complex operational data into actionable insights, analytical solutions, and optimization opportunities that improve network performance, efficiency, and responsiveness

This role partners closely with Distribution Center and Contact Center Operations, Engineering, Technology, and other cross-functional teams to develop and implement analytical capabilities that support operational decisions, identify opportunities for improvement, and enable smarter, more efficient operations for our customers and brands.

What You'll Do

• Develop and implement analytical models, algorithms, tools, and automated processes that improve operational performance and decision-making across DC/CC network
• Analyze operational and supply chain data to identify trends, root causes, and opportunities to improve productivity, capacity, service, and cost
• Translate complex data into clear, actionable insights and recommendations for Operations and functional leaders.
• Partner with Operations, Engineering, Technology, and other cross-functional teams to develop and implement scalable analytical and optimization solutions.
• Leverage AI, machine learning, automation, forecasting, and advanced analytics to simplify work and optimize network performance.
• Measure the effectiveness and business impact of analytical solutions and recommend enhancements to drive continuous improvement.
• Deploy machine learning algorithms in production environment.

Who You Are

• Degree in Computer Science, Data Science, Engineering, Mathematics, Statistics, or a related quantitative field.
• 9+ years 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 both at a detailed level as well as to summarize findings and extrapolate knowledge to make strong recommendations for change
• Ability to collaborate with cross functional teams and influence product and analytics roadmap.