Applied Scientist, AWS Support

DESCRIPTION

AWS Sales, Marketing, and Global Services (SMGS) is responsible for driving revenue, adoption, and growth from the largest and fastest growing small- and mid-market accounts to enterprise-level customers including public sector.

We are a new team in AWS' Kumo organisation - a combination of software engineers and AI/ML experts.

Kumo is the software engineering organization that scales AWS's support capabilities. Amazon's mission is to be earth's most customer-centric company and this also applies when it comes to helping our own Amazon employees with their everyday IT Support needs. Our team is innovating for the Amazonian, making the interaction with IT Support as smooth as possible. We achieve this through multiple mechanisms which eliminate root causes altogether, automate issue resolution or point customers towards the optimal troubleshooting steps for their situation. We deliver the support solutions plus the end-user content with instructions to help them self-serve. We employ machine learning solutions on multiple ends to understand our customer's behavior, predict customer's intent, deliver personalized content and automate issue resolution through chatbots.

As an applied scientist on our team, you will help to build the next generation of case routing using artificial intelligence to optimize business metric targets addressing the business challenge of ensuring that the right case gets worked by the right agent within the right time limit whilst meeting the target business success metric. You will develop machine learning models and pipelines, harness and explain rich data at Amazon scale, and provide automated insights to improve case routing that impact millions of customers every day. You will be a pragmatic technical leader comfortable with ambiguity, capable of summarizing complex data and models through clear visual and written explanations.

Key job responsibilities

1. Analyze complex support case datasets and metrics to drive insight
2. Design, build, and deploy effective and innovative ML solutions to optimize case routing
3. Evaluate the proposed solutions via offline benchmark tests as well as online A/B tests in production
4. Drive collaborative research and creative problem solving across science and engineering team
5. Propose and validate hypothesis to deliver and direct our product road map
6. Work with engineers to deliver low latency model predictions to production

BASIC QUALIFICATIONS

1. 4+ years of CS, CE, ML or related field experience
2. 3+ years of building models for business application experience
3. Experience programming in Java, C++, Python or related language
4. Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing
5. Degree in Computer Science / Computer Engineering / Machine Learning / a related field

PREFERRED QUALIFICATIONS

1. Experience using Unix/Linux
2. Experience in professional software development
3. Masters or PhD in Computer Science / Computer Engineering / Machine Learning / a related field
4. Experience in patents or publications at top-tier peer-reviewed conferences or journals

Amazon is an equal opportunities employer, and we value your passion to discover, invent, simplify and build. We welcome applications from all members of society irrespective of age, sex, disability, sexual orientation, race, religion or belief.