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Applied Scientist, Prime Video Science

Amazon.com Inc

  • Seattle, WA
  • 4 days ago
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    Skills

    • Artificial Intelligence (AI)unmatched
    • Communication Skillsunmatched
    • Cross-Functionalunmatched
    • Customer Experienceunmatched
    • Customer Responseunmatched
    • Customer/Client Researchunmatched
    • Customer/Consumer Behaviorunmatched
    • Data Modelingunmatched
    • Data Scienceunmatched
    • Deep Learningunmatched
    • Detail Orientedunmatched
    • Entertainment and Mediaunmatched
    • Experiment Designunmatched
    • Financeunmatched
    • LifeTime Value (LTV)unmatched
    • Machine Learningunmatched
    • Model Validationunmatched
    • Production Systemsunmatched
    • Profit & Lossunmatched
    • Prototypingunmatched
    • Reinforcement Learningunmatched
    • Resolve Customer Issuesunmatched
    • Software Engineeringunmatched

    Description

    The Prime Video Science team leverages the latest in machine learning and AI techniques combined with causal inference to bring scientific rigor to the biggest decisions in entertainment: what content to make, what to license, and where to invest. We build large-scale models that simulate how our global customer base responds to change, and we get to see that work shape what the business does. Prime Video is an industry-leading entertainment business and a critical driver of Amazon Prime subscriptions, contributing to customer loyalty and lifetime value. Our models learn from customer behavior to answer questions the business can"t test directly and use those answers to guide where Prime Video invests in content and product. We"re looking for an Applied Scientist to help build the next generation of these models.

    As an Applied Scientist on this team, you will build machine learning and deep learning models on large-scale global data to simulate customer behavior across the business. Ideally you bring experience with reinforcement learning, causal inference, and/or the design of agentic AI systems. You will partner closely with business, finance, engineering, and science stakeholders to take ideas from concept and prototype through to production. The candidate should have strong communication skills and the ability to translate data-driven findings into actionable insights. The successful candidate will be a self-starter comfortable with ambiguity, with strong attention to detail and the ability to work in a fast-paced and ever-changing environment.

    Key job responsibilities

    • Build models that simulate customer behavior to answer counterfactual "what-if" questions that guide major content and product investment decisions.
    • Apply deep learning, reinforcement learning, causal inference, and experimental design to large-scale customer data to model how customers respond to change.
    • Design and prototype agentic AI systems and other novel ML approaches and research new methods to improve the accuracy and scale of our models.
    • Validate and calibrate models against real-world randomized experiments, and partner with software engineers to deliver scalable, production-ready systems.
    • Translate model outputs into clear recommendations and communicate results to business, finance, and science stakeholders through both technical papers and business-facing documents.

    About the team

    The Prime Video Science team is a multidisciplinary group of applied scientists, data scientists, economists, and engineers. We take on some of the hardest research questions in the business, and our work carries visibility up to the CFO/CEO level. We pursue ambitious research at the intersection of machine learning, AI, and causal inference, turning that research into innovations that improve customer experience and strengthen business profitability. Few science teams get to work on problems this hard and this impactful; if that combination excites you, we"d love to talk.

    Numbers & Facts

    LocationSeattle, 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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