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Applied Scientist - Optimization, Amazon Transportation

Amazon.com Inc

  • Bellevue, WA
  • 4 days ago
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    Skills

    • Algorithmsunmatched
    • Analysis Skillsunmatched
    • Business Modelunmatched
    • Calendar Managementunmatched
    • Capacity Managementunmatched
    • Code Reviewsunmatched
    • Data Analysisunmatched
    • Demand Forecasting/Planningunmatched
    • Design Documentunmatched
    • Machine Learningunmatched
    • Network Designunmatched
    • Operations Researchunmatched
    • Optimization Algorithmunmatched
    • Performance Managementunmatched
    • Performance Modelingunmatched
    • Process Improvementunmatched
    • Product Engineeringunmatched
    • Production Systemsunmatched
    • Prototypingunmatched
    • Scientific Researchunmatched
    • Simulationunmatched
    • Technical/Engineering Designunmatched
    • Testingunmatched
    • Time Managementunmatched
    • Transportation Routingunmatched
    • Truckload Freightunmatched
    • Vehicle Fleetsunmatched
    • Warehousingunmatched

    Description

    Amazon"s Middle Mile Surface Research Science seeks an Applied Scientist to invent and build optimization models and algorithm to improve how Amazon plans and operates its transportation network.

    Amazon"s transportation network moves millions of truckloads of freight between vendors, warehouses, and customers using a fleet of trucks, trains, and airplanes, on time and at low cost. Operating it requires constant decisions about how to route, schedule, and balance capacity across the network, and our strategy is to make those decisions with science-driven technology. Because existing techniques rarely fit Amazon"s scale and unique business needs, this role centers on inventing new approaches and algorithms.

    As an Applied Scientist, you"ll develop optimization models and algorithms. Your role will initially focus on driver capacity optimization. Your models will impact business decisions worth billions of dollars and improve the delivery experience for millions of customers.

    Key job responsibilities

    • Design and develop optimization models and algorithms that enhance our optimization and planning systems.
    • Build models and algorithms from prototype to production-level systems.
    • Translate ambiguous business problems into modeling approaches, and drive the technical design with product, engineering, and operations partners.
    • Influence key business decisions through rigorous modeling and analysis.
    • Communicate results and recommendations to scientific and business audiences.

    A day in the life

    • Analyze data to investigate a business problem or model performance and identify improvements
    • Brainstorm new algorithmic strategies or business opportunities with fellow scientists
    • Leverage GenAI to build and test your new model features
    • Run a simulation or experiment to evaluate your model's performance
    • Meet with product and tech partners to review project requirements, data, design, or other project decisions
    • Review code changes or a design document from a fellow scientist or engineers
    • Write and present a paper documenting algorithm features, results, and recommendations

    About the team

    Middle Mile Surface Research Science builds the models and algorithms that plan and operate Amazon"s middle mile network. Our work spans operations research, optimization, and machine learning. We work on vehicle route planning, capacity planning, scheduling, network design, transit-time prediction, demand forecasting, and equipment re-balancing. Our team of about ten scientists is part of a broader science organization whose scientists bring deep expertise in machine learning and optimization. We optimize decisions worth billions of dollars and reach millions of customers.

    Numbers & Facts

    LocationBellevue, 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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