Sr. Program Manager, WW Benchmarking and Scorecard (GSCE)

Amazon"s Global Standards & Customer Excellence (GSCE) organization owns the Worldwide Scorecard - the mechanism that provides a holistic view of operational performance across Safety, People, Customer Experience, Quality, Cost, and Sustainability pillars for 1,000+ last-mile delivery stations and sort centers spanning North America, Europe, Japan, India, and ECCF. The WW Benchmarking team within GSCE manages performance benchmarking using the Continuous Benchmarking Rate Setting (CBRS) methodology - clustering stations into peer groups and setting statistically rigorous performance targets that control for non-ops factors.

As the Senior Program Manager for the Quality Pillar, you will own end-to-end benchmarking and scorecard strategy for First Pass Yield (FPY), Stow Buffer Compliance, and emerging quality metrics across all regions. You will drive the CBRS methodology for quality KPIs, launch and scale benchmarking studies that close performance gaps at underperforming stations, develop next-generation metrics that replace legacy measurements, and feed input-level KPIs into the Risk Engine that powers predictive operational alerts. You will partner with Operations, ACES, BIE (Analytics), and Finance teams to ensure quality benchmarks are accurate, equitable, and drive measurable operational improvement across stations worldwide.

This role requires strong analytical thinking, program management rigor, and the ability to translate complex statistical methodologies into operator-friendly insights. You will manage multiple concurrent workstreams - from quarterly benchmark refreshes, to multi-month benchmarking studies with site-level interventions, to expanding quality benchmarks to new regions and business units where none previously existed. You will also build AI-powered tooling that accelerates validation and delivery, and contribute input signals to the Gravion Risk Engine. Cross-team coordination, data fluency, stakeholder communication to senior leadership, and a bias for automation are essential.

You will be a strong partner of Central and Field ACES teams - delivering operator sentiment of the metrics, benchmarking the metrics and aligning closely with their OP process, initiating metric changes, and maintaining metric parity around the world.

Key job responsibilities

• Own the Quality Pillar benchmarking portfolio end-to-end - vision, methodology, and cadence for FPY, Stow Buffer Compliance, and future quality metrics across NA, EU, JP, ECCF, RSR, and RoW
• Drive benchmarking methodology for quality KPIs - quarterly benchmark generation, cluster design, sub-cluster coefficients, and statistical model improvement
• Design benchmarking studies identifying root causes at underperforming stations, sharing best practices, and driving measurable quality improvement
• Expand quality benchmarks to new regions and BUs - adapting methodology for local data, gaining alignment, and launching benchmarks where none existed
• Own Road to CBRS (benchmarking) for quality metrics - translating benchmarks into actionable station-level insights that close the gap
• Partner with Central and Field ACES on operator sentiment, OP alignment, and worldwide metric parity
• Define upstream quality KPI signals for the Risk Engine - early-warning indicators and data integration partnership
• Build AI-powered validation tooling - cluster analyzers, anomaly detection, and self-service analytics for operators
• Partner with BIE on data pipeline requirements - freshness, accuracy, and scalability in Andes/Redshift
• Present insights, study results, and methodology recommendations to senior leadership and cross-functional stakeholders
• Write quality pillar narratives for quarterly publications and stakeholder newsletters

A day in the life

• Monday: Review CBRS cluster refresh - identify sub-cluster movements, flag quality KPI anomalies, prep stakeholder insights. Tuesday: Triage Asana intakes, meet operators to answer benchmark and cluster placement questions.
• Mid-week: Strategic alignment with stakeholders on metric logic, long-term vision, and network performance. Meet cross-BU stakeholders on benchmarking expansion needs for quality metrics.
• Thursday: Deep methodology work - review site outliers per Quality Pillar KPI, discuss logic changes with regional stakeholders, assess network impact.
• Friday: Document weekly quality benchmarking performance, update study progress, share best practices from top stations, field operator gap-closure questions.

Amazon offers a full range of benefits that support you and eligible family members, including domestic partners and their children. Benefits can vary by location, the number of regularly scheduled hours you work, length of employment, and job status such as seasonal or temporary employment.

The benefits that generally apply to regular, full-time employees include:

• Medical, Dental, and Vision Coverage
• Maternity and Parental Leave Options
• Paid Time Off (PTO)
• 401(k) Plan

If you are not sure that every qualification on the list above describes you exactly, we"d still love to hear from you!

At Amazon, we value people with unique backgrounds, experiences, and skillsets. If you're passionate about this role and want to make an impact on a global scale, please apply!

About the team

The WW Benchmarking & Standards team establishes the performance truth for Amazon"s global last mile network - defining what "good" looks like across 1,000+ delivery stations through statistically validated benchmarks and engineering-grade standards. We set the rates that drive labor planning decisions, publish the WW Scorecard that holds stations accountable to peer-adjusted targets, and run multi-month benchmarking studies that convert underperformance into quantified improvement opportunities.

Our CBRS methodology clusters stations into statistically comparable peer groups, removing excuses and surfacing true operational gaps. We are expanding from retrospective measurement into predictive performance engineering - building risk engines, self-service analytics, and AI-powered tooling that tell operators not just where they stand, but what to do next. The team operates at the intersection of data science, program management, and field operations.