Job Description
Amazon's Selection Monitoring team is responsible for making the biggest catalog on the planet even bigger by powering the World Product Catalog. Our systems process billions of products to algorithmically find products not already sold on Amazon and programmatically add them to the Amazon catalog. We apply parallel processing, machine learning and deep learning algorithms to evaluate products and brands in order to identify and prioritize products and brands we should add to Amazon's catalog. Teams across Amazon worldwide consume our datasets and systems to improve: product information, search and discoverability, pricing, and delivery experience. Our work involves building state-of-the-art Information Retrieval (IR) systems to mine the web and automatically create structured entities from un-structure/semi-structured data. We constantly stretch the boundaries of large-scale distributed systems, Elastic Computing, Big Data, and SOA technologies to tackle challenges at Amazon's global scale.
Come join us in our journey to make everything - and yes, we do mean everything - that anyone wants to buy, available on Amazon!
The ideal candidate will have excellent product management, program management, problem solving and communication skills and be comfortable interacting with technical and non-technical stakeholders at all levels. In addition, the ability to work backwards and think about the program from a customer perspective is crucial.
Key job responsibilities
- Understand your customers and their pain points; work with your users and stakeholders to find solutions that help them enable their scenarios.
- Drive execution of cross-team and cross-org projects from inception to launch, formulate product vision and strategy, define and prioritize road maps, define user stories.
- Work closely with software development teams on defining, designing and delivering high-quality products; provide feedback on architecture, design, and priorities.
- Engage with teams across Amazon to evangelize your team"s products and build relationships.
- Identify, assess and mitigate risks, provide escalation management, anticipate and make trade-offs balancing the business needs vs. constraints
- Clearly communicate plan and project status to management and key technical and business stakeholders
Numbers & Facts
| Location | Seattle, WA |
| Industry | Retail |
| Company Size | 10,000 employees or more |
| Year Founded | 1994 |
| Website | http://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
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
- Algorithmsunmatched
- Big Dataunmatched
- Communication Skillsunmatched
- Data Setsunmatched
- Deep Learningunmatched
- Distributed Computingunmatched
- Establish Prioritiesunmatched
- IR (Infrared)unmatched
- Information Retrievalunmatched
- Large-Scale Systemsunmatched
- Machine Learningunmatched
- Parallel Computingunmatched
- Pricingunmatched
- Problem Solving Skillsunmatched
- Product Managementunmatched
- Product Strategyunmatched
- Product Testingunmatched
- Product/Service Launchunmatched
- Project/Program Managementunmatched
- Risk Analysisunmatched
- Risk Managementunmatched
- Salesunmatched
- Service-Oriented Architecture (fka Distributed Object Architecture)unmatched
- Software Developmentunmatched
- Structured Dataunmatched
- Technical Leadershipunmatched
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