Senior Research Scientist, AWS Compute Optimizer, AWS Insights

Key Skills

Java Programming, Python Programming, SQL, AWS, R Programming

Job Description

Job summary

Would you like to help us build the next-generation cloud services that will power the largest managed infrastructure in the world? We’re hiring a Data Scientist for AWS Compute Optimizer team within Amazon AWS Insights. Our service uses large amounts of data combined with machine learning (ML) and push the boundaries of scale, availability, and performance, while maintaining the highest standards for security and operational excellence.

AWS Compute Optimizer helps you choose optimal configurations for three types of AWS resources: Amazon EC2 instances, Amazon EBS volumes, and AWS Lambda functions, based on your utilization data. By applying the knowledge drawn from Amazon’s own experience running diverse workloads in the cloud, Compute Optimizer identifies workload patterns and recommends optimal AWS resources. Compute Optimizer analyzes the configuration and resource utilization of your workload to identify dozens of defining characteristics, for example, if a workload is CPU-intensive, if it exhibits a daily pattern, or if a workload accesses local storage frequently. The service processes these characteristics and identifies the hardware resource required by the workload. Compute Optimizer infers how the workload would have performed on various hardware platforms (e.g. Amazon EC2 instances types) or using different configurations (e.g. Amazon EBS volume IOPS settings, and AWS Lambda function memory sizes) to offer recommendations.

You will take on challenges in providing recommendations based on billions of metric records available for various customers and their use cases. You will be empowered to think big, invent on behalf of our customers, make judgment calls and find elegant solutions to hard problems.

Read more about AWS Compute Optimizer https://aws.amazon.com/compute-optimizer/

Key job responsibilities

• Technical lead for the scientist team to build statistical and ML recommendation models
• Drive collaborative research and creative problem solving across science and engineering team
• Analyze complex datasets to drive insight
• Propose and validate hypothesis to deliver and direct our product road map
• Work with engineers to deliver low latency model predictions to production
• Constructively critique peer research and mentor junior scientists and engineers

BASIC QUALIFICATIONS

• Master's degree in Mathematics, Statistics or in any another highly quantitative field
• 5+ years of research experience in a quantitative domain
• 5+ years of experience in using Python, R, or similar languages
• Track record dealing with complex and ambiguous problems that drive business value
• Deep understanding of regression modeling, forecasting techniques, time series analysis, machine-learning concepts such as supervised and unsupervised learning
• Proficiency in model development, model validation and model implementation for large-scale applications
• Ability to communicate technical concepts and solutions at a level appropriate for technical and non-technical audiences
• Experience with extraction, processing, filtering, and presenting large data quantities (1M+ rows) via AWS technologies, SQL, and data pipelines
• Ability to translate business requirements into science problems. Independently define problem formulation and create scalable solutions

PREFERRED QUALIFICATIONS

• Experience collaborating with software engineering teams
• Track record innovating using machine learning and statistical algorithms
• Track record of implementing and deploying large scale machine learning applications and tools
• 8+ years of experience as Machine Learning Scientists and/or Research Scientists