Amazon Web Services is the largest consumer cloud offering in the world, powering cutting-edge science, rapidly growing startups, and industry leaders. The AWS Reliability Engineering team builds the systems and services that ensure that AWS customers can rely on the highest-availability, lowest-latency cloud platform on the planet. If you are looking for a position where you can wrangle data to directly impact the infrastructure relied upon by millions of people very day, then we'd love to hear from you.
Our success depends on our ability to process huge amounts of data to determine the health of AWS across its various services and products. We build highly available services that use a variety of technologies, including high speed data processing, Machine Learning and highly customizable automation engines, to detect and mitigate operational issues before they impact customers. A successful candidate will be passionate about data, having the ability to manipulate large amounts of data in order to build models that can be used to build the next generation of reliability detection and response systems.
In this position, you will research and develop innovative machine learning based approaches to predict the near-term future. You will have ownership over our data strategy, working in one of the world's most diverse and complex data environments, bringing together loosely structured datasets to find actionable outcomes that improve our customer's experience. You should have deep expertise in processing and manipulating huge amounts of data, both historical and in real-time as well as experience working as part of a dev team to productize your findings.
The right candidate will possess excellent business and communication skills, be able to work with engineers as well as business owners to formulate our data strategy and drive its execution across the globe.
- Develop quantitative models across multiple reliability data slices for use in Machine Learning and other systems
- Develop hypotheses, design experiments, collaborate with engineering team to implement live tests and evaluate their performance
- Answer complex business questions by using appropriate statistical techniques on available data or designing and running experiments to gather data
- Manage critical processes that are central to the delivery of accurate results (e.g. data pipelines, etc.)
- Communicate findings to managers and engineers, often through succinct written summaries of findings and code samples