Director, Data Science, Amazon Customer Service Network Solutions

Amazon; Seattle (WA); On-site; USD 250,000 - 338,000; Full time

Job summary

Amazon in Seattle seeks a Director of Data Science for the Customer Service Network Solutions to build and lead a unified data, analytics, and measurement function across human-assisted and AI-enabled customer channels. You will set the data strategy, recruit a multidisciplinary team, and partner across CS and central data organizations to enable scalable, value-driven decision making.

This role shapes how we plan capacity, route customers, develop associates, and allocate resources, balancing

Qualifications

• MS in a STEM field or related technical degree.
• Proven track record building and leading data science or analytics teams at scale.
• Experience translating data and science into business impact.
• Experience leading cross-functional teams and influencing senior leaders.

Responsibilities

• Build and lead the Network Solutions data and analytics organization.
• Develop a unified measurement framework and valuation methods.
• Own data foundation, pipelines, and data quality governance.
• Drive adoption of standards and integration into production systems.
• Interface with central data organizations and senior stakeholders.
• Develop long-term data science roadmaps for scale.

Skills

Executive leadership

Cross-functional collaboration

Strategic partnerships

Data science leadership

Education

MS in STEM field

PhD in STEM field

Job description

Director, Data Science, Amazon Customer Service Network Solutions

Job ID: 10495083 | Amazon.com Services LLC

We are seeking a seasoned executive leader to join our Network Solutions team within Amazon Customer Service, as Director, Data Science. In this role you will build and lead a data, analytics, and measurement science function that orchestrates Amazon's Customer Service full network – across our human-assisted and customer-facing automation AI-enabled channels – as a single intelligent system. Network Solutions owns demand forecasting, network planning, routing, real-time observability, and workforce strategy, and is building the next generation of AI-enabled planning systems with intelligent and adaptive capabilities that consider humans and AI-agents, simultaneously. You will lead a multi-disciplinary team – scientists, data engineers, business intelligence engineers, and analysts – who will build the data strategy these new systems require and the measurement science that reshapes how every network decision is made. At the core is a unified measurement framework that measures the value of experiences across customers, associates, and our business, drawing on causal inference, economics, operations, and behavioral science. You will create the underlying logic for how we plan capacity, route customers, develop associates, and allocate resources – and serve as an interface and work closely with partner teams within Customer Service, including the CS-wide Data Intelligence organization. The ideal candidate brings deep cross-disciplinary experience in data science, measurement, and operations – a track record of building and leading data and insights organizations from 0-to-1, the scientific depth to drive novel measurement frameworks, and the rare ability to blend quantitative rigor with an understanding of human systems – developing the right logic to drive decision-making at scale.

Key job responsibilities

• Build and lead the Network Solutions data and analytics organization: provide unified leadership across business intelligence engineering, data engineering, analytics, and reporting; recruit, grow, and retain a team spanning measurement scientists, data engineers, and analysts, building the function from 0-to-1
• Drive the measurement science and decisioning core: develop the causal inference-based framework that quantifies value creation across multiple dimensions; establish methodology standards, signal definitions, and utility function design that give Network Solutions a unified view of performance
• Own the Network Solutions data foundation: own critical signal pipelines, govern data quality, and build a composable data architecture that all Network Solutions product and science teams build on; ensure measurements are interoperable across planning, routing, incident management, and workforce systems
• Integrate measurement science into production systems: demonstrate the shift to value-informed decision-making; partner with product and engineering teams to embed measurement frameworks into planning, routing, and resource allocation
• Interface with Amazon CS and company-wide data, analytics, and science organizations: represent Network solutions as a peer partner to central data infrastructure, customer experience measurement, and applied science functions; consolidate Network Solutions data demand into a clear, prioritized voice
• Drive adoption of data standards and measurement frameworks: translate complex models and multi-dimensional utility functions into intuitive, actionable insights for non-technical stakeholders; establish shared measurement standards that teams across the organization can build on
• Develop the long-term data and science roadmap: anticipate future needs as the organization scales; identify opportunities to extend measurement capabilities beyond Network Solutions

About the team

Network Solutions sits at the intersection of customer experience and associate experience within Amazon Customer Service, owning the logic and infrastructure that determines how those two sides are balanced, served, and optimized together. On one side is the customer: their experience, their journey, and the AI automation that increasingly shapes both. On the other side is the associate: their work, their well-being, and the conditions that make them effective. Network Solutions sits at the center, owning demand forecasting, network planning, routing and matching, real-time observability, and workforce strategy – including the long‑term design of the network itself as the balance between AI and human engagement continues to evolve. We are building the next generation of systems that will transform how Customer Service operates using intelligent, adaptive capabilities that learn and improve continuously.

Basic Qualifications

• MS in a STEM field – industrial engineering, operations research, statistics, computer science, economics, or a related technical field
• Track record of leading the design and delivery of scientific or analytical frameworks that have influenced organizational decision-making at scale
• Demonstrated experience building and leading multi-disciplinary data organizations – including data engineering, business intelligence, and analytics functions – ideally from 0-to-1
• Experience serving as a strategic partner to senior business leaders and cross-functional peers, translating data and science capabilities into business impact

Preferred Qualifications

• PhD in a STEM field – industrial engineering, operations research, statistics, computer science, economics, or a related technical field
• 15+ years of relevant experience after PhD spanning data science, measurement science, analytics, or operations research
• Cross-disciplinary background spanning two or more of: measurement science, causal inference, industrial engineering, behavioral economics, human factors, operations research, or business intelligence
• Experience building data and insights organizations within customer service, customer support, or operations domains at global scale
• Familiarity with causal inference methods, utility function design, or value measurement frameworks applied to service operations or network optimization
• Experience as a primary liaison between a domain-specific data organization and centralized data, science, or analytics functions – consolidating demand, aligning roadmaps, and building durable partnerships
• Background in usability research, associate experience design, or behavioral science – bringing human-centered methods into operational decision-making
• Experience building and governing analytics and reporting infrastructure, including ownership through transitions in centralized data services
• Demonstrated ability to lead without authority across organizational boundaries, bridging science, product, engineering, and operations teams

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.

The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits .

USA, WA, Seattle - 250,000.00 - 338,200.00 USD annually