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Applied Scientist, Last Mile Science

Amazon.com Inc

  • Austin, TX
  • 13 days ago

    Highlights

    Invent and design novel solutions for scientifically complex problem areas, and identify opportunities for invention within existing and new business initiatives. Our planning and routing intelligence systems drive billions of daily decisions - enabling safe, efficient, and frustration-free routes for drivers across the globe.

    Numbers & Facts

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

    Description

    Are You Ready to Redefine How the World Receives Its Packages?

    What if your algorithms defined the most efficient path for millions of deliveries - every single day? At Amazon, we"re building the science that makes that possible, and we"re looking for exceptional scientists to help lead the way.

    The Last Mile Routing & Planning organization develops the software, algorithms, and tools that power the "magic" of home delivery. Our planning and routing intelligence systems drive billions of daily decisions - enabling safe, efficient, and frustration-free routes for drivers across the globe.

    What You"ll Do

    In this role, you"ll sit at the intersection of state-of-the-art research and real-world impact. You will:

    • Design and build algorithms that solve large-scale, complex logistics problems
    • Synthesize data from diverse sources to identify high-value business opportunities
    • Provide research direction and data-driven insights to guide strategic decisions
    • Translate complex technical approaches into clear communication for scientists, engineers, and business stakeholders
    • Partner closely with scientists and engineers in a collaborative, high-impact environment

    What You"ll Work On

    We have an exciting and growing portfolio of research areas, including:

    • Routing for same-day and grocery deliveries
    • Planning for electric and autonomous vehicles
    • District-level and stop-level planning
    • Forecasting solutions for diverse delivery programs

    All of this is powered by the latest methods in Operations Research (OR), Machine Learning (ML), and Generative AI - at a truly global scale. Successful candidates will lead one or more of these problem spaces.

    What We"re Looking For

    • Deep expertise in Operations Research and/or Machine Learning methods
    • Proven experience applying these methods to large-scale, real-world business problems
    • Ability to translate models into production-ready code in Python or Java
    • Strong communication skills - you can explain complex technical concepts to diverse audiences
    • A bias for action and an iterative mindset when tackling ambitious research challenges

    Why Amazon

    We"re passionate about your growth. Whether you want to explore emerging technologies, take on broader scope, or accelerate your career trajectory, we"ll invest in helping you get there. Our business is scaling fast - and so are the opportunities for the people who build it.

    If you"re driven by the challenge of optimizing one of the world"s most complex logistics systems and excited to see your work impact millions of customers daily, we"d love to hear from you.

    Key job responsibilities

    • Invent and design novel solutions for scientifically complex problem areas, and identify opportunities for invention within existing and new business initiatives
    • Deliver large-scale, high-impact solutions to complex problems in support of medium-to-large business goals
    • Shape the design of scientifically complex software systems, personally contributing significant portions of the critical scientific novelty
    • Apply mathematical optimization, machine learning, and Generative AI techniques to develop solution methodologies for in-house decision support tools and software
    • Research, prototype, simulate, and experiment with models - and actively participate in their production-level deployment in Python or Java
    • Engage with the broader scientific community by publishing research articles and participating in leading research conferences

    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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