ML scientists at Amazon participate in the design, development, evaluation, deployment and updating of data-driven models and analytical solutions for machine learning (ML) and time-series forecasting applications. Develop and/or apply statistical modeling techniques (e.g. Bayesian models and deep neural networks), optimization methods, and other ML techniques to different applications in business and engineering. Routinely build and deploy ML models on available data. Research and implement novel ML and statistical approaches to add value to the business. Mentor junior engineers and scientists.
The AWS Demand Forecasting and Planning team is responsible for growing the world's largest Cloud. We forecast customer demand, build ML systems that understand customer needs, and drive utilization improvement for all AWS services.
What we own:
· Building a world-class forecasting platform that scales to handling billions of time series data in real time.
· Developing predictive customer analytics models and recommendation engines.
· Expanding inventory replenishment models and systems for each AWS service in the fast-growing AWS product portfolio.
· Finding out the optimal tradeoff between AWS service availability and fleet utilization.
· Driving fleet utilization improvement where each 1% means tens of millions of additional free cash flow.
· Automating tactical and strategic capacity planning tools to optimize for service availability and infrastructure cost.
What you will learn:
· State of the art forecasting methodologies.
· Application of machine learning to large-scale customer analytics.
· Inventory management and supply chain management for the Cloud.
· Resource management and admission control for the Cloud.
· The internals of all AWS services.
Note that location is flexible between our Bellevue and Seattle offices.
Forecasting, Statistics, Machine Learning, Optimization, Inventory Management, Supply Chain Management, AWS, Cloud, Cloud Computing, EC2, S3, EBS, DynamoDB, CloudFront, Java, C++, Object Oriented, R, Distributed Systems, High Availability, Scalability, Concurrent
· PhD or foreign equivalent in Computer Science, Machine Learning, Statistics, or a related field and five years of work or research experience in the job offered or a related occupation or a Master's Degree or foreign equivalent in Computer Science, Machine Learning, Statistics, or a related field and nine years of research or work experience in the job.
· Experience in the following skill(s): programming in Java, C++, Python, or equivalent programming language; and conducting the analysis and development of various supervised and unsupervised machine learning models for moderately complex projects in business, science, or engineering.
· 2+ years of industry experience.
· Ability to communicate effectively across multiple organizations in the company
· Experience with time-series forecasting and recommendation systems
· Strong knowledge of statistics and probability
· Strong knowledge of model design, selection, and hypothesis testing
· Programming experience in Java/Scala
· Experience with SQL/noSQL databases to manage and analyze large data sets
Amazon is an Equal Opportunity Employer – Minority / Women / Disability / Veteran / Gender Identity / Sexual Orientation / Age