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Sr. Applied Scientist, Customer Behavior Analytics (Marketing Measurement Solutions)

Amazon.com Inc
  • Seattle, WA
    23 days ago

    Job Description

    Amazon's Customer Behavior Analytics org is looking for an Applied Scientist to spearhead the rapid growth of our Marketing Measurement solutions. The team focuses on building scalable ML and causal inference solutions to estimate the effectiveness of Amazon marketing efforts and provide actionable insights to the various marketing teams within Amazon. This is a high-impact role with opportunities to develop systems that affect investments to the size of billions of dollars. We work closely with business stakeholders and strive to continuously produce tangible impact on the company's strategic and tactical planning and operations.

    A successful candidate will be a self-starter, comfortable with ambiguity, able to think big and be creative, while still paying careful attention to detail. You should be able to translate how data represents the customer journey, be comfortable dealing with large and complex data sets, and have experience using machine/deep learning at scale to solve business problems. You should have strong analytical and communication skills, be able to work with product managers and software teams to define key business questions and work with the analytics team to solve them. You will apply your expertise in ML/DL, statistics, and data-wrangling to identify opportunities for further research and to provide insights that drive larger initiatives. You will join a highly collaborative and diverse working environment that will empower you to shape the future of Amazon marketing, as well allow you to be part of the large science community within the Customer Behavior Analytics (CBA) organization.

    Key job responsibilities

    The main responsibilities for this position include:

    • Apply your expertise in Transformer models, LLMs, ML/DL and statistical modeling to develop solutions and systems that describe how Amazon's marketing campaigns impact customers' actions
    • Own the end-to-end development of novel causal inference models that address the most pressing needs of our business stakeholders and help guide their future actions
    • Improve upon and simplify our existing solutions and frameworks
    • Review and audit modeling processes and results from other scientists, both junior and senior
    • Work with marketing leadership to align our measurement plan with business strategy
    • Formalize assumptions about how our models are expected to behave and explain why they are reasonable
    • Identify new opportunities that are suggested by the data insights - Bring a department-wide perspective into decision making
    • Develop and document scientific research to be shared with the greater science community at Amazon

    About the team

    The Customer Behavior Analytics (CBA) organization owns Amazon's insights pipeline, from data collection to deep analytics. We aspire to be the place where Amazon teams come for answers, a trusted source for data and insights that empower our systems and business leaders to make better decisions. Our outputs shape Amazon product and marketing teams' decisions and thus how Amazon customers see, use, and value their experience.

    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
    • Business Planunmatched
    • Business Strategyunmatched
    • Communication Skillsunmatched
    • Customer/Consumer Behaviorunmatched
    • Data Collectionunmatched
    • Data Setsunmatched
    • Deep Learningunmatched
    • Detail Orientedunmatched
    • Leadershipunmatched
    • Machine Learningunmatched
    • Marketingunmatched
    • Marketing Campaignunmatched
    • Marketing Softwareunmatched
    • Model Reviewunmatched
    • Problem Solving Skillsunmatched
    • Process Modelingunmatched
    • Product Marketingunmatched
    • Scalable System Developmentunmatched
    • Scientific Publicationsunmatched
    • Scientific Researchunmatched
    • Statistical Modelingunmatched
    • Statisticsunmatched
    • Strategic Planningunmatched
    • Tactical Operationsunmatched
    • Team Playerunmatched

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