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Data Scientist II, Amazon Fulfillment Technology (AFT) Science

Amazon.com Inc

  • Bellevue, WA
  • 6 days ago
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    Skills

    • Analysis Skillsunmatched
    • Bug Tracking/Defect Managementunmatched
    • Data Analysisunmatched
    • Data Scienceunmatched
    • Establish Prioritiesunmatched
    • Experiment Designunmatched
    • Forecastingunmatched
    • Machine Learningunmatched
    • Metricsunmatched
    • Operations Processesunmatched
    • Operations Researchunmatched
    • Order/Customer Fulfillmentunmatched
    • Performance Managementunmatched
    • Performance Modelingunmatched
    • Process Flowunmatched
    • Process Improvementunmatched
    • Production Systemsunmatched
    • Python Programming/Scripting Languageunmatched
    • SQL (Structured Query Language)unmatched
    • Scala Programming Languageunmatched
    • Scalable System Developmentunmatched
    • Simulationunmatched
    • Software Engineeringunmatched
    • Statistical Modelingunmatched
    • Statisticsunmatched
    • Technical Supportunmatched
    • Use Casesunmatched

    Description

    The Amazon Fulfillment Technologies (AFT) Science team is looking for an exceptional Data Scientist, with strong analytical skills and understanding of optimization, to partner with scientists, engineers, product managers, and operations leaders, and develop data-driven solutions for one of the most complex systems in the world: Amazon's Fulfillment Network. At AFT Science, we design, build and deploy optimization, simulation, and machine learning solutions to power the production systems running at world wide Amazon Fulfillment Centers. We solve a wide range of problems that are encountered in the network, including labor planning and staffing, demand prioritization, stow guidance, pick scheduling, and flow process optimization. We are tasked to develop innovative, scalable, and reliable science-driven solutions that are beyond the published state of art in order to run frequently (ranging from every few minutes to every few hours per use case) and continuously in our large scale network.

    Key job responsibilities

    As an Data Scientist, you will work with other scientists, software engineers, product managers, and operations leaders to develop scientific solutions and analytics using a variety of tools and observe direct impact to process efficiency and associate experience in the fulfillment network. Key responsibilities include:

    • Design and conduct rigorous experimental design for production pilots to evaluate the impact of the solution and improve model performance
    • Lead the end-to-end lifecycle of forecasting models, from research and experimentation through production launch including defining success metrics, obtaining stakeholder sign-off, and managing rollout
    • Develop and deploy production grade ML and statistical models using Python, Scala, SQL, and related tools
    • Perform large-scale exploratory data analysis to uncover patterns, identify opportunities, and inform model development
    • Translate complex science findings into clear insights and recommendations for technical and non-technical stakeholders at all levels
    • Contribute to Amazon"s scientific community and the broader research field through collaboration and presentation in top-tier venues

    About the team

    Amazon Fulfillment Technology (AFT) designs, develops and operates the end-to-end fulfillment technology solutions for all Amazon Fulfillment Centers (FC). We harmonize the physical and virtual world so Amazon customers can get what they want, when they want it.

    The AFT Science team has expertise in operations research, optimization, statistics, simulation, and machine learning. We also have domain expertise in the operational processes within the FCs and their defects. We prioritize advancements that support AFT tech teams and focus areas rather than specific fields of research or individual business partners. We influence each stage of innovation from inception to deployment which includes both developing novel solutions or improving existing approaches. Resulting production systems rely on a diverse set of technologies, our teams therefore invest in multiple specialties as the needs of each focus area evolves.

    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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