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Data Scientist II, Data Scientist, Decision Science

Amazon.com Inc

  • Sunnyvale, CA
  • 7 days ago

    Highlights

    As a Data Scientist II on our Devices forecasting team, you will answer that question by building econometric and machine learning models that project long-term demand, assess the incrementality of new products, and quantify willingness to pay for specific features. Build and validate econometric and machine learning models that generate long-term demand forecasts for Amazon Devices, selecting the right methodology based on data characteristics and business context.

    Numbers & Facts

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

    Description

    What will customers want from Amazon Devices one, two, or three years from now? As a Data Scientist II on our Devices forecasting team, you will answer that question by building econometric and machine learning models that project long-term demand, assess the incrementality of new products, and quantify willingness to pay for specific features. Your analysis will directly shape portfolio decisions, helping product managers decide what to build next. This is a team that is investing in AI to accelerate how science informs business strategy, making now a particularly exciting time to join.

    Key job responsibilities

    • Build and validate econometric and machine learning models that generate long-term demand forecasts for Amazon Devices, selecting the right methodology based on data characteristics and business context.
    • Assess the incrementality of new products and quantify willingness to pay for product features, translating model outputs into clear narratives that help product managers adjust their portfolio strategy.
    • Collaborate with product managers, engineers, and business stakeholders to scope analytical projects, define metrics, and identify the data requirements needed to answer ambiguous forecasting questions.
    • Communicate findings to technical and non-technical audiences through clear documentation, effective visualizations, and well-structured presentations that drive informed decisions.
    • Mentor less experienced data scientists through code reviews, knowledge sharing, and active participation in scientific discussions and team planning.

    A day in the life

    You might spend your morning refining a demand forecast model, testing how a new product feature variable improves prediction accuracy. After lunch, you could be walking product managers through your incrementality analysis and aligning on what the numbers mean for their roadmap. Later, you might review a teammate"s willingness-to-pay study or experiment with an AI-based approach to accelerate your modeling pipeline. Your work moves between deep independent analysis and collaborative sessions where you translate complex results into actionable recommendations.

    About the team

    Our team owns long-term forecasting and product analytics for Amazon Devices. We build the science that tells the story of where customer demand is headed and what drives it. You will work alongside scientists, engineers, and product managers who value rigorous analysis and practical impact. We are currently expanding our use of AI to accelerate how we deliver insights, and we are looking for people who are curious, collaborative, and ready to help shape that direction.

    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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