Amazon.com Inc logo

Applied Scientist , PAE

Amazon.com Inc

  • Seattle, WA
  • 22 days ago

    Highlights

    The PAE Data Science team builds AI-native intelligence systems that improve payment experience, optimize marketing efficiency, automate operational workflows, and enable faster business decision-making across the payments ecosystem. Do you want to build models that directly move billions in revenue - predicting payment risk before it happens, recommending the right payment method at the right moment, and eliminating friction that customers shouldn"t have to think about?.

    Numbers & Facts

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

    Description

    Every time a customer checks out, a split-second decision determines which payment method appears, in what ranking, whether there is payment failure risk and how frictionless the experience feels. That decision touches 300MM+ customers and 2B+ monthly transactions - and you"ll be the scientist building the intelligence behind it.

    Are you excited by the challenge of applying machine learning, GenAI, and real-time personalization to one of the highest-volume, lowest-latency decision systems at Amazon? Do you want to build models that directly move billions in revenue - predicting payment risk before it happens, recommending the right payment method at the right moment, and eliminating friction that customers shouldn"t have to think about?

    Join Payment Acceptance & Experience (PAE) Data Science, where you"ll build the ML systems that power Amazon"s Payment Experience Intelligence. You"ll take models from conception to production alongside scientists, engineers, and product managers, shipping at a scale few teams in the industry can match.

    Key job responsibilities

    • Build and ship ML systems at scale - design, develop, evaluate, deploy, and monitor ML models that personalize payment experiences for 300MM+ customers across 2B+ monthly transactions.
    • Solve global problems once - develop worldwide models that scale across business lines and locales with minimal adaptation, and continuously improve model performance and ML architecture.
    • Own the full lifecycle - contribute production-grade code and science tooling, from experimentation framework to deployed inference.
    • Measure real impact - design A/B experiments, conduct rigorous statistical analysis, and translate results into product and business decisions.
    • Ship with engineering and product partners - collaborate with SDEs to take models from prototype to production, and with business stakeholders to drive alignment on science-informed strategy.
    • Advance the science - present and publish research internally and externally, contributing to Amazon"s science community and raising the bar for the field.ommunity

    About the team

    Payment Acceptance and Experience"s (PAE) mission is to build the most trusted, intuitive, and accessible payment experience on earth. The team provides new and existing customers, anywhere in the world, the ability to pay on- and off-Amazon, with world-class ease of use, payment method variety, and security. The PAE Data Science team builds AI-native intelligence systems that improve payment experience, optimize marketing efficiency, automate operational workflows, and enable faster business decision-making across the payments ecosystem. It serves as a high-leverage, strategic engine advancing PAE"s mission.

    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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