Amazon Applied Scientist II Devices Forecasting Science 

United States, Washington, Seattle 

981220540

In this role, you will have an opportunity to both develop advanced scientific solutions, and drive critical customer and business impact. You will play a key role to drive end-to-end solutions from understanding our business requirements, exploring a large amount of historical data and ML models, building prototypes and exploring conceptually new solutions, to working with partner teams for prod deployment. You will collaborate closely with scientists, engineering peers as well as business stakeholders. You will be at the heart of a growing and exciting focus area for Amazon Devices and Services.We are looking for an individual with outstanding analytical abilities, excellent communication skills, and someone who is comfortable working with cross-functional teams and systems. You will be responsible for researching, prototyping, experimenting, analyzing predictive models and developing smart automation solutions.Key job responsibilities
· Research and develop new methodologies for demand forecasting, alarms, alerts and automation with advanced models and methods.
· Build and maintain codebase, upholding engineering best practices
· Improve upon existing methodologies by adding new data sources and implementing model enhancements.
· Drive scalable and hands-off-the-wheel solutions.
· Create and track accuracy and performance metrics (both technical and business metrics).
· Create, enhance, and maintain technical documentation, and present to other scientists, engineers and business leaders.
· Drive best practices on the team; mentor and guide junior members to achieve their career growth potential.

- 3+ years of building models for business application experience
- PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience
- Experience programming in Java, C++, Python or related language
- Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing

- Experience using Unix/Linux
- Experience in professional software development