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Data Scientist, Fire TV

Amazon.com Inc
  • Seattle, WA
    4 days ago

    Job Description

    Fire TV is reshaping the way millions of people discover, engage with, and enjoy entertainment every day. The Fire TV, Advertising and Appstore Decision Science organization is looking for a Data Scientist who is passionate about using data to surface customer insights that will influence the development of new and improved customer experiences across the Fire TV organization.

    This role contributes to the foundational science and analytics capabilities used by Product, Finance, Marketing, Advertising, and Engineering teams to make high-quality business decisions. You will design, develop, and operationalize data science solutions supporting Fire TV customer engagement and retention, lifecycle analytics, Ads monetization, experimentation, and AI-enabled analytics.

    This role is appropriate for a scientist who can independently own data science workstreams, partner effectively across technical and business teams, and deliver high-quality solutions with minimal guidance. The ideal candidate combines strong quantitative fundamentals with practical experience applying machine learning and statistical methods to real-world business problems. Successful scientists in this role deliver trusted models and analyses, improve measurement quality, communicate findings clearly to technical and non-technical audiences, and help the business move faster through data-driven insight.

    Key job responsibilities

    • Design, develop, validate, and maintain machine learning models, statistical analyses, and decision frameworks supporting one or more of the following pillars: Fire TV engagement, lifecycle analytics, ads monetization, and Appstore performance
    • Independently own data science workstreams with guidance on ambiguous or high-impact decisions. Deliver analyses and models from problem definition through validation and handoff, partnering with senior scientists and stakeholders as needed
    • Build and refine customer segmentation and clustering frameworks that enable personalized marketing and engagement strategies
    • Contribute to the design of A/B experiments and analyses; develop power analyses, define guardrail and success metrics, and interpret results to inform product decisions
    • Partner with Business Intelligence Engineers, Data Engineers, Product, Finance, and Marketing stakeholders to translate business questions into rigorous analytical frameworks
    • Identify and close measurement gaps - including coverage gaps in customer attribution, engagement, and conversion - and advocate for better instrumentation upstream
    • Communicate findings clearly and accurately to both technical and non-technical audiences; write rigorous technical documents and present results with appropriate caveats
    • Contribute to DS best practices including reproducibility, code quality, documentation, and model validation standards
    • Mentor junior data scientists and analysts on methodology, tool usage, and analytical approach

    About the team

    The FAA Decision Science team turns trusted insights into business actions that accelerate growth, improve customer experiences, and optimize engagement and monetization across Fire TV, Advertising, and Appstore. We operationalize insights into scalable decision systems through durable data products, advanced modeling, automation, and AI-enabled workflows. Our team is comprised of Data Engineers, Business Intelligence Engineers, Data Scientists, and Product Managers who take pride in building reliable, trustworthy data products that empower our stakeholders to make data-driven decisions. We encourage scientists who are curious about the business, care deeply about data quality, and want to grow their craft in a collaborative, high-ownership environment.

    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

    Skills

    • Advertisingunmatched
    • Analysis Skillsunmatched
    • Artificial Intelligence (AI)unmatched
    • Automationunmatched
    • Best Practicesunmatched
    • Business Intelligenceunmatched
    • Communication Skillsunmatched
    • Customer Experienceunmatched
    • Customer Retention/Renewalunmatched
    • Customer/Client Researchunmatched
    • Data Analysisunmatched
    • Data Qualityunmatched
    • Data Scienceunmatched
    • Decision Supportunmatched
    • Documentation Modelsunmatched
    • Engagement Marketingunmatched
    • Equipment Maintenance/Repairunmatched
    • Federal Aviation Administration (FAA)unmatched
    • Financeunmatched
    • Instrumentationunmatched
    • Machine Learningunmatched
    • Market Segmentationunmatched
    • Marketingunmatched
    • Marketing Strategyunmatched
    • Mentoringunmatched
    • Metricsunmatched
    • Model Validationunmatched
    • Operations Planningunmatched
    • Quality Managementunmatched
    • Quality Metricsunmatched
    • Statistical Modelingunmatched
    • Statisticsunmatched
    • Systems Scalabilityunmatched
    • Team Playerunmatched
    • Technical Presentationunmatched
    • Technical Writingunmatched
    • Television Advertisingunmatched
    • Usage Analysisunmatched

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