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Senior Manager, Applied Science, Network Planning SolutionsAmazon.com Services LLC • Seattle, Washington, United States
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Senior Manager, Applied Science, Network Planning Solutions

Amazon.com Services LLC
  • US
    Seattle, Washington, United States
  • US
    Seattle, Washington, United States
Jetzt Bewerben

Über

Have you ever wondered what it takes to transform millions of manual network planning decisions into AI-powered precision? Network Planning Solutions is looking for scientific innovators obsessed with building the AI/ML intelligence that makes orchestrating complex global operations feel effortless. Here, you'll do more than just build models; you'll create 'delight' by discovering and deploying the science that delivers exactly what our customers need, right when they need it. If you're ready to transform complex data patterns into breakthrough AI capabilities that power intuitive human experiences, you've found your team.
Network Planning Solutions architects and orchestrates Amazon's customer service network of the future. By building AI-native solutions that continuously learn, predict and optimize, we deliver seamless customer experiences and empower associates with high-value work—driving measurable business impact at a global scale.
As a Sr. Manager, Applied Science, you will own the scientific innovation and research initiatives that make this vision possible. You will lead a team of applied scientists and collaborate with cross-functional partners to develop and implement breakthrough scientific solutions that redefine our global network.
Key job responsibilities
Lead AI/ML Innovation for Network Planning Solutions:
- Develop and deploy production-ready demand forecasting algorithms that continuously sense and predict customer demand using real-time signals
- Build network optimization algorithms that automatically adjust staffing as conditions evolve across the service network
- Architect scalable AI/ML infrastructure supporting automated forecasting and network optimization capabilities across the system
Drive Scientific Excellence:
- Build and mentor a team of applied scientists to deliver breakthrough AI/ML solutions
- Design rigorous experiments to validate hypotheses and quantify business impact
- Establish scientific excellence mechanisms including evaluation metrics and peer review processes
Enable Strategic Transformation:
- Drive scientific innovation from research to production - Design and validate next-generation AI-native models while ensuring robust performance, explainability, and seamless integration with existing systems.
- Partner with Engineering, Product, and Operations teams to translate AI/ML capabilities into measurable business outcomes
- Navigate ambiguity through experimentation while balancing innovation with operational constraints
- Influence senior leadership through scientific rigor, translating complex algorithms into clear business value
A day in the life
Your day will be a dynamic blend of scientific innovation and strategic problem-solving. You'll collaborate with cross-functional teams, design AI algorithms, and translate complex data patterns into intuitive solutions that drive meaningful business impact.
About the team
We are Network Planning Solutions, a team of scientific innovators dedicated to reshaping how global service networks operate. Our mission is to create AI-native solutions that continuously learn, predict, and optimize customer experiences. We empower our associates to tackle high-value challenges and drive transformative change at a global scale.
BASIC QUALIFICATIONS- 10+ years of building large-scale machine learning and AI solutions at Internet scale experience
- Master's degree in Computer Science (Machine Learning, AI, Statistics, or equivalent)
- Experience building large-scale machine learning and AI solutions at Internet scale
- Experience distilling informal customer requirements into problem definitions, dealing with ambiguity and competing objectives
- Experience hiring and leading experienced scientists as well as having a successful record of developing junior members from academia or industry to a successful career track
PREFERRED QUALIFICATIONS- 10+ years of practical work applying ML to solve complex problems for large-scale applications experience
- 5+ years of hands-on work in big data, machine learning and predictive modeling experience
- 5+ years of people management experience
- PhD in Computer Science (Machine Learning, AI, Statistics, or equivalent)
- Experience in practical work applying ML to solve complex problems for large scale applications
- Experience developing, deploying and managing AI products at scale
- Experience building complex highly-scalable systems that involve predictive models or applications of machine learning
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 - 218,800.00 - 295,900.00 USD annually
  • Seattle, Washington, United States

Sprachkenntnisse

  • English
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