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Applied Scientist II, International and Emerging Stores Payments

Amazon.com Inc

  • Seattle, WA
  • 19 days ago

    Highlights

    We build solutions that directly shape how customers pay and that drive conversion across Amazon"s fast-growing international markets-and there is no shortage of hard science and engineering problems, since these markets span most of the world"s countries and the majority of its customers. What you will work on: Build models that recommend the most suitable payment method for each customer-for example installments, cards, or local payment options-and identify the right customers to reach, balancing customer preference, cost, and risk.

    Numbers & Facts

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

    Description

    Do you want to translate innovative science into products that expand financial access for millions? At International and Emerging Stores Payments (IESP), we build payment solutions for communities and geographies that Amazon"s selection and prices do not yet reach because of payment barriers. These markets make up roughly 80% of the world"s countries and 85% of its population.

    As an Applied Scientist II on our team, you will design, build, and ship machine learning and generative-AI solutions that remove those barriers and advance financial inclusion, working at the intersection of research and production alongside scientists, engineers, and economists. If you are a curious, self-motivated researcher who turns ambiguity into clarity, we would like to hear from you.

    What you will work on:

    • Build models that recommend the most suitable payment method for each customer-for example installments, cards, or local payment options-and identify the right customers to reach, balancing customer preference, cost, and risk.
    • Take models to production behind a real-time, low-latency personalization layer that serves live shopping traffic at scale.
    • Build multi-agent generative-AI systems that turn unstructured inputs-customer feedback, documents, and operational data-into reliable, decision-ready insight, with verification that guards against model hallucination.
    • Help customers discover and adopt installments and alternative payment methods.
    • Design and analyze large-scale online experiments and causal measurement to validate real customer and business impact.

    Key job responsibilities

    • Design, develop, and evaluate machine learning and deep learning models, and deploy production-ready solutions to complex customer and business problems.
    • Conduct rigorous scientific research: form hypotheses, run experiments, evaluate model performance, and iterate on approaches within your domain of expertise.
    • Write clean, maintainable, and efficient code that integrates smoothly into larger systems and meets a high bar for operational excellence.
    • Partner with engineering to take your models to production, and with scientists across related payments ML teams to solve shared, complex problems.
    • Contribute to team roadmaps, priorities, and technical direction; mentor peers and provide constructive feedback on research and code.
    • Publish at peer-reviewed venues and file patent applications where appropriate.

    A day in the life

    You will start your day reviewing experiment results and refining model architectures based on new insights. Throughout the day you will alternate between writing research code, analyzing data, and discussing technical approaches with teammates, working closely with engineering to build your ideas and take them to production. You will regularly present findings and propose new ideas, and you may write research papers and submit patent applications.

    About the team

    We are the science team for International and Emerging Stores Payments. We build solutions that directly shape how customers pay and that drive conversion across Amazon"s fast-growing international markets-and there is no shortage of hard science and engineering problems, since these markets span most of the world"s countries and the majority of its customers. We value scientific rigor, creative problem-solving, and a genuine commitment to learning and growth. If you are excited about building impactful solutions and advancing financial inclusion through applied science, we would love to have you join us.

    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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