Amazon.com Inc logo

Sr Applied Scientist, Amazon Supply Chain

Amazon.com Inc

  • Seattle, WA
  • 6 days ago
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    Skills

    • A/B Testingunmatched
    • Algorithmsunmatched
    • Amazon Web Services (AWS)unmatched
    • Architectural Analysisunmatched
    • Artificial Intelligence (AI)unmatched
    • Best Practicesunmatched
    • Business Solutionsunmatched
    • Cloud Computingunmatched
    • Code Reviewsunmatched
    • Customer Relationsunmatched
    • Data Modelingunmatched
    • Deep Learningunmatched
    • Demand Forecasting/Planningunmatched
    • Emerging Technologyunmatched
    • Enterprise Applicationsunmatched
    • Machine Learningunmatched
    • Mentoringunmatched
    • Metricsunmatched
    • Model Validationunmatched
    • Modeling Languagesunmatched
    • Product Managementunmatched
    • Production Systemsunmatched
    • Requirements Managementunmatched
    • Scientific Publicationsunmatched
    • Startupunmatched
    • Supply Chainunmatched
    • Supply Chain Management Softwareunmatched
    • Supply Chain Operationsunmatched
    • Technical Strategyunmatched

    Description

    As part of the AWS Applied AI Solutions organization, we have a vision to provide business applications, leveraging Amazon"s unique experience and expertise, that are used by millions of companies worldwide to manage day-to-day operations. We will accomplish this by accelerating our customers" businesses through delivery of intuitive and differentiated technology solutions that solve enduring business challenges. We blend vision with curiosity and Amazon"s real-world experience to build opinionated, turnkey solutions. Where customers prefer to buy over build, we become their trusted partner with solutions that are no-brainers to buy and easy to use.

    We are looking for a Senior Applied Scientist to join our team that is building revolutionary enterprise applications leveraging machine learning, generative AI, and agentic AI to help millions of companies worldwide manage their day-to-day supply chain operations. Our mission is to accelerate our customers" businesses through intuitive, differentiated technology solutions that solve enduring supply chain challenges. We blend strategic vision with curiosity and Amazon"s real-world operational experience to build opinionated, turnkey solutions that make the "buy versus build" decision a no-brainer for our customers.

    As a Senior Applied Scientist, you will design and develop state-of-the-art machine learning models and algorithms that power intelligent supply chain applications at global scale. You will work at the intersection of research and real-world product impact-translating scientific breakthroughs into production systems that serve millions of customers. We operate like a startup within AWS, offering you the opportunity to tackle unprecedented challenges while working with the latest technologies in deep learning, large language models, and optimization.

    If you are passionate about pushing the boundaries of applied science, thrive in ambiguous problem spaces, and want to shape the future of supply chain intelligence while having the backing of AWS"s extensive resources, we want to hear from you.

    Key job responsibilities

    • Design, develop, and deploy novel machine learning models for demand forecasting, inventory optimization, anomaly detection, and supply chain decision-making.
    • Lead the development of GenAI and Agentic AI solutions that automate complex supply chain workflows and deliver intelligent, adaptive recommendations to customers.
    • Formulate real-world business problems as machine learning problems; define data requirements, model architectures, evaluation metrics, and experimentation frameworks.
    • Drive end-to-end applied science projects from ideation through experimentation, offline evaluation, A/B testing, and production deployment at scale.
    • Publish research findings in top-tier conferences (NeurIPS, ICML, KDD, AAAI) and file patents to advance Amazon"s intellectual property.
    • Mentor and develop junior scientists; raise the technical bar for the science team through code reviews, design reviews, and knowledge sharing.
    • Collaborate closely with engineering, product management, and business stakeholders to translate scientific capabilities into customer-facing product features.
    • Influence the technical strategy and scientific roadmap for the organization; identify new areas of investment and emerging opportunities in AI/ML.
    • Establish and promote best practices for experimentation, model validation, and responsible AI development across the team.

    About the team

    The AWS Applied AI Solutions team builds enterprise applications that leverage Amazon"s operational expertise to solve real-world supply chain challenges for millions of companies. We operate like a startup within AWS-moving fast, shipping iteratively using state-of-the-art AI technologies. We invest in your growth through mentorship from senior scientists, conference publication support, and internal science reading groups. Amazon values diverse experiences-even if you don"t meet all preferred qualifications, we encourage you to apply. If your career hasn"t followed a traditional path, don"t let that stop you.

    ABOUT AWS:

    Diverse Experiences

    Amazon values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn't followed a traditional path, or includes alternative experiences, don't let it stop you from applying.

    Why AWS

    Amazon Web Services (AWS) is the world's most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating - that's why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.

    Work/Life Balance

    We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why flexible work hours and arrangements are part of our culture. When we feel supported in the workplace and at home, there's nothing we can't achieve in the cloud.

    Inclusive Team Culture

    Here at AWS, it's in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity and AmazeCon conferences, inspire us to never stop embracing our uniqueness.

    Mentorship and Career Growth

    We're continuously raising our performance bar as we strive to become Earth's Best Employer. That's why you'll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.

    Numbers & Facts

    LocationSeattle, WA
    IndustryRetail
    Company Size10,000 employees or more
    Year Founded1994
    Websitehttp://Amazon.com/militaryroles

    About Company

    At Amazon, we don’t wait for the next big idea to present itself. We envision the shape of impossible things and then we boldly make them reality. So far, this mindset has helped us achieve some incredible things. Let’s build new systems, challenge the status quo, and design the world we want to live in. We believe the work you do here will be the best work of your life.

    Wherever you are in your career exploration, Amazon likely has an opportunity for you. Our research scientists and engineers shape the future of natural language understanding with Alexa. Fulfillment center associates around the globe send customer orders from our warehouses to doorsteps. Product managers set feature requirements, strategy, and marketing messages for brand new customer experiences. And as we grow, we’ll add jobs that haven’t been invented yet.

    It’s Always Day 1
    At Amazon, it’s always “Day 1.” Now, what does this mean and why does it matter? It means that our approach remains the same as it was on Amazon’s very first day – to make smart, fast decisions, stay nimble, invent, and stay focused on delighting our customers. In our 2016 shareholder letter, Amazon CEO Jeff Bezos shared his thoughts on how to keep up a Day 1 company mindset. “Staying in Day 1 requires you to experiment patiently, accept failures, plant seeds, protect saplings, and double down when you see customer delight,” he wrote. “A customer-obsessed culture best creates the conditions where all of that can happen.” You can read the full letter here

    Our Leadership Principles
    Our Leadership Principles help us keep a Day 1 mentality. They aren’t just a pretty inspirational wall hanging. Amazonians use them, every day, whether they’re discussing ideas for new projects, deciding on the best solution for a customer’s problem, or interviewing candidates. To read through our Leadership Principles from Customer Obsession to Bias for Action, visit https://www.amazon.jobs/principles

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