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Senior Data Scientist, Amazon Stores Finance Science, Amazon Stores Finance Science

Amazon.com Inc

  • Seattle, WA
  • 30+ days ago
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    Skills

    • Biologyunmatched
    • Communication Skillsunmatched
    • Constructionunmatched
    • Data Analysisunmatched
    • Data Modelingunmatched
    • Data Scienceunmatched
    • Economicsunmatched
    • Financeunmatched
    • Financial Modelingunmatched
    • Financial Planningunmatched
    • Forecastingunmatched
    • Industry Standardsunmatched
    • Leadershipunmatched
    • Problem Solving Skillsunmatched
    • Process Improvementunmatched
    • Product Developmentunmatched
    • Product Engineeringunmatched
    • Project Lifecycleunmatched
    • Scalable System Developmentunmatched
    • Software Engineeringunmatched
    • Statistical Modelingunmatched

    Description

    WW Amazon Stores Finance Science (ASFS) works to leverage science and economics to drive improved financial results, foster data-backed decisions, and embed science within Finance. ASFS is focused on developing products that empower controllership, improve business decisions and financial planning by understanding financial drivers, and innovate science capabilities for efficiency and scale.

    We are looking for a data scientist to lead high-visibility initiatives for forecasting Amazon Stores financials. You will develop new science-based forecasting methodologies and build scalable models to improve financial decision-making and planning for senior leadership up to VP and SVP level. You will build new ML and statistical models from the ground up that aim to transform financial planning for Amazon Stores.

    We prize creative problem solvers with the ability to draw on an expansive methodological toolkit to transform financial decision-making with science. The ideal candidate combines data-science acumen with strong business judgment. You have versatile modeling skills and are comfortable owning and extracting insights from data. You are excited to learn from and alongside seasoned scientists, engineers, and business leaders. You are an excellent communicator and effectively translate technical findings into business action.

    Key Job Responsibilities

    • Demonstrating thorough technical knowledge, effective exploratory data analysis, and model building using industry-standard ML models • Working with technical and non-technical stakeholders across every step of science project life cycle • Collaborating with finance, product, data engineering, and software engineering teams to create production implementations for large-scale ML models • Innovating by adapting new modeling techniques and procedures • Presenting research results to our internal research community

    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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