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Applied Scientist II, Predictive Targeting

Amazon.com Inc
  • Seattle, WA
    27 days ago

    Job Description

    Are you passionate about using data and machine learning to improve how Amazon reaches customers? The Customer Targeting team is looking for an Applied Scientist to build the science behind the targeting of Amazon"s marketing initiatives across channels and ad formats. You will turn business questions into modeling problems and take your solutions from prototype to production, working closely with senior scientists, engineers, and business partners.

    We are moving targeting toward outcome-based optimization and an AI-native, agentic way of working. In this role you will work on online optimization and reinforcement learning, incrementality modeling, and the next generation of our segment-based targeting model. You will also help build agentic workflows that make targeting decisions transparent and bring science recommendations to the people using them.

    The right candidate has strong quantitative and statistical skills, hands-on experience with modern ML methods, and is comfortable working through ambiguity in a fast-paced environment. You pay close attention to detail, learn quickly, and work well in a highly collaborative team.

    Key job responsibilities

    • Build online optimization (e.g., TSO, bandits) and reinforcement learning methods that optimize targeting decisions for business outcomes rather than proxy metrics.
    • Develop incrementality and uplift models that estimate the causal impact of targeting, and use them to improve who we target and how much we spend.
    • Improve the existing segment-based targeting model: engineer and evaluate new features, migrate it to new model architectures, and build automated feedback loops that retrain and improve the model from observed outcomes.
    • Contribute to the intelligence layer of our agentic system: build components that explain targeting decisions and propose science-driven solutions to business partners.
    • Design and analyze experiments (A/B tests, causal inference methods) to measure the incremental impact of targeting changes.
    • Write production-quality model code and partner with engineers to deploy, monitor, and maintain models.
    • Present methods and results clearly, backed by data, with actionable recommendations for science and business stakeholders.

    About the team

    Predictive Targeting builds the systems that decide who sees Amazon"s marketing content, and how often, across Amazon"s stores and channels. We are engineers and scientists working on one shared problem: making sure customers see the most relevant and engaging marketing, and making each campaign better than the last.

    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

    • A/B Testingunmatched
    • Analysis Skillsunmatched
    • Artificial Intelligence (AI)unmatched
    • Business Modelunmatched
    • Campaignsunmatched
    • Channel Marketingunmatched
    • Detail Orientedunmatched
    • Experiment Designunmatched
    • IBM TSO/ISPFunmatched
    • Machine Learningunmatched
    • Marketingunmatched
    • Metricsunmatched
    • Prototypingunmatched
    • Quantitative Analysisunmatched
    • Reinforcement Learningunmatched
    • Team Playerunmatched

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