Amazon.com Inc logo

Data Scientist, Experience Analytics

Amazon.com Inc
  • Seattle, WA
    5 days ago

    Job Description

    AWS is seeking a Data Scientist to join our Consumer Experience team. We"re looking for someone who is curious about large-scale data challenges and motivated to apply ML/AI and advanced analytics to solve real customer problems.

    Reporting to the Science Lead, this role supports the analytical capabilities of AWS by applying emerging technologies, contributing to data science best practices, and partnering with stakeholders to deepen understanding of the AWS customer experience.

    The ideal candidate has experience working in complex data and analytics environments, with hands-on skills in Machine Learning and advanced analytics techniques - preferably within cloud computing. You should be comfortable building models and equally comfortable explaining what they mean to a non-technical audience.

    Key job responsibilities

    • Apply statistical analysis, ML, and complex data mining techniques to deliver insights that shape the AWS customer experience.
    • Build production-ready analytics solutions that support effective business decisions.
    • Partner with product, engineering, and design teams to develop and launch data products.
    • Contribute to the adoption of Gen AI and ML-based approaches across the data science practice, including building proof-of-concept AI-driven customer use cases.
    • Communicate technical findings clearly to both technical and non-technical stakeholders.
    • Bring new ideas - share approaches, tools, and methods that raise the bar for the team.

    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

    • Amazon Web Services (AWS)unmatched
    • Analysis Skillsunmatched
    • Artificial Intelligence (AI)unmatched
    • Best Practicesunmatched
    • Business Supportunmatched
    • Cloud Computingunmatched
    • Communication Skillsunmatched
    • Customer Experienceunmatched
    • Data Analysisunmatched
    • Data Miningunmatched
    • Data Scienceunmatched
    • Emerging Technologyunmatched
    • Machine Learningunmatched
    • Product Engineeringunmatched
    • Product/Service Launchunmatched
    • Proof of Conceptunmatched
    • Resolve Customer Issuesunmatched
    • Statisticsunmatched
    • Use Casesunmatched

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