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Applied Scientist, AWS Infrastructure Services Science

Amazon.com Inc
  • Herndon, VA
    10 days ago

    Job Description

    AWS Infrastructure Services Science (AISS) researches and builds machine learning models that influence the power utilization at our data centers to ensure the health of our thermal and electrical infrastructure at high infrastructure utilization.

    As an Applied Scientist, you will work on our Science team and partner closely with other scientists, data engineers and Software teams to accurately model and optimize our power infrastructure. Outputs from your models will directly influence our data center topology and will drive exceptional cost savings. You will be responsible for researching and deploying machine learning models that optimize our power and thermal infrastructure, working across AWS to solve data mapping and quality issues and contribute to our Science team vision.

    You are skeptical. When someone gives you a data source, you pepper them with questions about sampling biases, accuracy, and coverage. When you're told a model can make assumptions, you proactively try to break those assumptions.

    You have passion for excellence. The wrong choice of data could cost the business dearly. You maintain rigorous standards and take ownership of the outcome of your data pipelines and code. You raise the bar on the software code standards to delivery faster and efficient solutions.

    You do whatever it takes to add value. You don't care whether you're building complex ML models, writing blazing fast code, integrating multiple disparate data-sets, or creating baseline models - you care passionately about stakeholders and know that as a curator of data insight you can unlock massive cost savings and preserve customer availability.

    You have a limitless curiosity. You constantly ask questions about the technologies and approaches we are taking and are constantly learning about industry best practices you can bring to our team.

    You have excellent business and communication skills to be able to work with product owners to understand key business questions and earn the trust of senior leaders. You will need to learn Data Center architecture and components of electrical engineering to build your models.

    You are comfortable juggling competing priorities and handling ambiguity. You thrive in an agile and fast-paced environment on highly visible projects and initiatives. The tradeoffs of cost savings and customer availability are constantly up for debate among senior leadership - you will help drive this conversation.

    This position requires superior analytical thinkers, able to quickly approach large ambiguous problems and apply their technical and statistical knowledge to identify opportunities for further research. You should be able to independently mine and analyze data, and be able to use any necessary programming and statistical analysis software to do so. Successful candidates must thrive in fast-paced environments which encourage collaborative and creative problem solving, be able to measure and estimate risks, constructively critique peer research, and align research focuses with the Amazon's strategic needs.

    Key job responsibilities

    • Leverage deep expertise in one or more scientific disciplines to invent solutions to ambiguous ads measurement problems
    • Disambiguate problems to propose clear evaluation frameworks and success criteria
    • Work autonomously and write high quality technical documents
    • Implement a significant portion of critical-path code, and partner with engineers to directly carry solutions into production
    • Work closely with other scientists to deliver impactful customer solutions
    • Share and publish works with the broader scientific community through meetings and conferences
    • Communicate clearly to scientific audiences

    Numbers & Facts

    LocationHerndon, VA
    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

    Skills

    • Amazon Web Services (AWS)unmatched
    • Analysis Skillsunmatched
    • Bar Code Softwareunmatched
    • Best Practicesunmatched
    • Communication Skillsunmatched
    • Conferencesunmatched
    • Cost Controlunmatched
    • Data Analysisunmatched
    • Data Managementunmatched
    • Data Mappingunmatched
    • Data Setsunmatched
    • Electrical Componentsunmatched
    • Electrical Engineeringunmatched
    • Electricityunmatched
    • Leadershipunmatched
    • Machine Learningunmatched
    • Multitaskingunmatched
    • Network Operations Centerunmatched
    • Problem Solving Skillsunmatched
    • Risk Analysisunmatched
    • Statistical Analysis System (SAS)unmatched
    • Statistical Programming Languagesunmatched
    • Statistics Softwareunmatched
    • Team Playerunmatched
    • Technical Writingunmatched
    • Topologyunmatched

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