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Senior Data Scientist, Customer Experience and Business Trends

Amazon.com Inc
  • Seattle, WA
    4 days ago

    Job Description

    Amazon"s Customer Experience and Business Trends (CXBT) organization is hiring a Senior Data Scientist for its Benchmarking, Economics, Analytics and Measurement (BEAM) team. BEAM"s mission is to improve customer experience across every Amazon business by turning fragmented internal and external data into decision-grade intelligence for senior leaders.

    This role anchors our Topline View of Retail initiative: an always-on competitive intelligence capability that fuses third-party transaction panels with Amazon"s internal signals to answer how Amazon is winning or losing share of wallet, across segments, categories, and time. You will not just analyze metrics - you will decide which metrics should exist, then build the statistical and machine learning models that generate, forecast, and explain them. Given a new business question and a pile of raw panel and internal data, you are the person who defines what "competitiveness" means, translates it into a defensible, reproducible metric and model, and defends the methodology to skeptical senior stakeholders.

    We are looking for someone with exceptional business judgment and metric intuition, paired with deep hands-on modeling skills: a strong point of view on what to measure, and the technical ability to build the models that measure it at scale. You should be equally comfortable pressure-testing a model"s assumptions and explaining its "so what" to a VP in two sentences.

    Key job responsibilities

    • Own the definition, methodology, and evolution of BEAM"s competitiveness metrics (e.g., share-of-wallet, segment-level penetration, price/selection/fulfillment competitiveness), including the trade-offs behind each definition.
    • Design, build, and validate statistical and machine learning models - forecasting, causal inference, segmentation, and anomaly detection - that power those metrics and surface competitive shifts.
    • Pull together disparate third-party transaction-panel data and internal Amazon signals into coherent, reproducible modeling pipelines that leadership can trust for recurring reporting.
    • Translate ambiguous business questions ("are we losing ground in grocery?") into the right metric, the right model, the right cut of data, and a clear, defensible answer.
    • Productionize models and analyses so they run reliably as recurring mechanisms, partnering with data engineers to scale and automate.
    • Produce monthly flash reports and deep-dive narratives that turn models and metrics into decisions for CXBT and business-line leadership.
    • Set the standard for analytical and modeling rigor on the team - methodology reviews, documentation, and guardrails against misleading cuts.
    • Mentor and technically uplift other scientists and BIEs on the team - reviewing modeling approaches and raising the bar on rigor (e.g., partnering with our Data Scientist on the MatchIQ model to strengthen methodology and validation).

    About the team

    CXBT is a group of diverse functions dedicated to understanding, improving, and influencing customer experience globally, across all of Amazon. We are builders who develop products, services, and data-driven approaches that shape offerings for nearly every Amazon business and customer type - consumers, developers, sellers, brands, employees, investors, streamers, and gamers. We work backwards from customer needs, combine technical and non-technical methods, and track industry and business trends. Our roles span Product Managers, Data Scientists, Economists, Business Intelligence Engineers, Data Engine, Applied Scentist, and Product Manager.

    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

    • Analysis Skillsunmatched
    • Benchmarkingunmatched
    • Business Intelligenceunmatched
    • Competitive Analysis/Strategyunmatched
    • Customer Experienceunmatched
    • Data Scienceunmatched
    • Documentationunmatched
    • Economic Analysisunmatched
    • Flash Reportingunmatched
    • Forecastingunmatched
    • Gamingunmatched
    • Industry/Trade Analysisunmatched
    • Leadershipunmatched
    • Machine Learningunmatched
    • Mentoringunmatched
    • Metricsunmatched
    • Model Reviewunmatched
    • Product Developmentunmatched
    • Product Managementunmatched
    • Retailunmatched
    • Salesunmatched

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