WFM Manager, LMAQ

Have you ever thought about what it takes to successfully deliver millions of packages to Amazon customers seamlessly every day like clock work? In order to make that happen, behind those millions of packages, billions of decisions get made by machines and humans. What is the accuracy of the customer provided address? Do we know exact location of the address on a Map? Is there a safe place to leave the package at? Can we make an unattended delivery? Would a signature be required? Is the address a commercial property? Do we know open business hours of the address? What if customer is not home? Is there an alternate delivery address? Does the customer have any special delivery preference? What are the other addresses that also have packages to be delivered on the same day? Are we optimizing the delivery associate’s route? Does the delivery associate know the locality well enough? Is there an access code to get inside the building? And the list simply goes on. At the core of it all is the underlying data that can help make those decisions in time. The Last Mile Analytics and Quality (LMAQ) team capitalizes on Amazon’s scale, speed, and ability to invent and simplify to accelerate the data flywheel and curate fresh and authoritative geospatial datasets to improve customer delivery experience. We work closely with tech and science teams on multiple initiatives to automate processes to operate at scale across all regions.

• Key job responsibilities
• Key Job Responsibilities
• •Drive end-to-end workforce management for the entire LMAQ space, designing and delivering short- and long-term labor planning strategies across all lines of business
• •Own forecasting, planning, and execution to ensure operational performance meets or exceeds targets
• •Build forecast models to drive headcount planning across spaces, programs, and sub-programs with high utilization, and cross-skilling optimization
• •Manage headcount planning across the space, ensuring key programs and business needs are driven without impacting SLA, sustaining operational performance with the least churn for managers
• •Ability to partner with multiple teams and build strong stakeholder relationships to drive HC planning for the LMAQ space
• •Manage the VCC vs. B&M mix across sites, ensuring compliance, driving seating planning across sites, and driving key operational metrics like cross-site reporting, etc.
• •Build a data-driven culture by championing automated solutions to drive LMAQ HC planning at a regular cadence with minimal effort
• •Own end-to-end delivery of multiple projects focused on performance optimization and cost efficiency
• •Guide the design, development, and maintenance of metrics, reports, analyses, and dashboards that inform key business decisions
• •Work through and influence WFM leads and analysts across each space without direct authority, aligning them to a common planning and execution standard
• •Demonstrate a strong eye for detail, uncovering trends, going beyond the obvious, and identifying root causes
• •Thrive in ambiguous environments and proactively take on new challenges
• •Influence hiring quality by raising the bar on interviewing standards across the organization

Basic qualifications

• - 7+ years of program or project management experience
• - Experience using data and metrics to determine and drive improvements
• - 7+ years of operational and/or retail management experience
• - Experience owning program strategy, end-to-end delivery, and communicating results to senior leadership

Preferred qualifications

• - 2+ years of driving process improvements experience
• - Master's degree, or MBA in business, operations, human resources, adult education, organizational development, instructional design or related field
• - Advanced degree in a quantitative field or an MBA
• - Ability to think strategically and drive the detailed execution of specific initiatives
• - Experience with workforce management tools and platforms (e.g., NICE, Verint, or proprietary systems)
• - Familiarity with capacity planning, scheduling optimization, or labor modeling at scale
• - Track record of delivering measurable cost savings or efficiency improvements

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