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Data Scientist, Amazon Devices, Devices Sales & Marketing

Amazon.com Inc

  • Bellevue, WA
  • 30+ days ago

    Highlights

    A successful candidate will be a problem solver who enjoys diving into data, is excited by difficult modeling challenges, is motivated to build something that will eventually become a production software system, and possesses strong communication skills to effectively interface between technical and business teams. We are a full stack science team that empowers product, marketing, and other business leaders to better understand customers who use Amazon devices, make decisions on product development or optimization, and measure the effectiveness of their efforts against our customers expectation.

    Numbers & Facts

    LocationBellevue, WA
    IndustryRetail
    Company Size10,000 employees or more
    Year Founded1994
    Websitehttp://Amazon.com/militaryroles

    Description

    The candidate in this role will own delivery of science products and solutions to help Amazon Devices Sales and Marketing org. make better decisions: product recommendations to customers, segmentation, financial incrementality of marketing initiatives, A/B testing etc.

    Key job responsibilities

    The Amazon Devices organization designs, produces and markets Echo Speakers, Kindle e-readers, Fire Tablets, Fire TV Streaming Media Players, Ring and Blink Smart Home & Security products. We are constantly looking to innovate on behalf of customers with new devices in existing or new categories or improving customer experience on existing platforms. The Devices Data Services (DDS) team provides Data Science, Analytics and Engineering support to the broader organization to enable Sales and Marketing activities across all these product lines.

    We are looking for an innovative, hands-on and customer-obsessed Data Scientist who can be a strategic partner to the product managers and engineers on the team. Our projects span multiple organizations and require coordination of experimentation, economic and causal analysis, and building predictive machine learning models. A successful candidate will be a problem solver who enjoys diving into data, is excited by difficult modeling challenges, is motivated to build something that will eventually become a production software system, and possesses strong communication skills to effectively interface between technical and business teams.

    In this role, you will be a technical expert with massive impact. You will take the lead on developing

    advanced ML systems that are key to reaching our customers with the right recommendations at the right time. Your work will directly impact the success of Amazon"s growing Devices business. You will work across diverse science/engineering/business teams. You will work on critical data science problems, building high quality, reliable, accurate, and consistent code sets that are aligned with our business needs.

    Key Performance Areas

    • Implement statistical or machine learning methods to solve specific business problems.
    • Improve upon existing methodologies by developing new data sources, testing model enhancements, and fine-tuning model parameters.
    • Directly contribute to development of modern automated recommendation systems
    • Build customer-facing reporting tools to provide insights and metrics to track model performance and explain variance
    • Collaborate with researchers, software developers, and business leaders to define product requirements, provide analytical support, and communicate feedback

    A day in the life

    You will work with other scientists, engineers, product managers, and marketers to develop new products that benefit our customers and help us reach our business goals. You will own solutions from end to end: conceptualization, prioritization, development, delivery, and productionalization.

    About the team

    We are a full stack science team that empowers product, marketing, and other business leaders to better understand customers who use Amazon devices, make decisions on product development or optimization, and measure the effectiveness of their efforts against our customers expectation. Our focus area is to build analytical frameworks that help the organization either access data, better understand the decisions customers are making and why, or assess customer satisfaction.

    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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