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Applied Scientist, BRP Payment Risk ML, BRP Payment Risk ML

Amazon.com Inc
  • San Diego, CA
    5 days ago

    Job Description

    Do you want to join an innovative team of scientists who use machine learning and statistical techniques to help Amazon provide the best customer experience by preventing eCommerce fraud?

    Are you excited by the prospect of analyzing and modeling terabytes of data and creating state-of-the-art algorithms to solve real world problems?

    Do you like to own end-to-end business problems/metrics and directly impact the profitability of the company? Do you enjoy collaborating in a diverse team environment?

    If yes, then you may be a great fit to join the Amazon Buyer Risk Prevention (BRP) Machine Learning group. We are looking for a talented scientist who is passionate to build advanced algorithmic systems that help manage safety of millions of transactions every day.

    Key job responsibilities

    Use machine learning and statistical techniques to create scalable risk management systems

    Learning and understanding large amounts of Amazon's historical business data for specific instances of risk or broader risk trends

    Design, development and evaluation of highly innovative models for risk management

    Working closely with software engineering teams to drive real-time model implementations and new feature creations

    Working closely with operations staff to optimize risk management operations,

    Establishing scalable, efficient, automated processes for large scale data analyses, model development, model validation and model implementation

    Tracking general business activity and providing clear, compelling management reporting on a regular basis

    Research and implement novel machine learning and statistical approaches

    Numbers & Facts

    LocationSan Diego, CA
    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

    • Algorithmsunmatched
    • Business Activity Monitoring (BAM)unmatched
    • Customer Experienceunmatched
    • Data Analysisunmatched
    • Data Modelingunmatched
    • Machine Learningunmatched
    • Management Reportingunmatched
    • Metricsunmatched
    • Model Validationunmatched
    • Problem Solving Skillsunmatched
    • Profit & Lossunmatched
    • Purchasing/Procurementunmatched
    • Riskunmatched
    • Risk Managementunmatched
    • Risk Modelingunmatched
    • Software Engineeringunmatched
    • Systems Administration/Managementunmatched
    • Systems Scalabilityunmatched
    • eCommerceunmatched

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