Amazon Applied Scientist Allocation Science 

United States, Washington, Seattle 

600300389

In this role, you will have an opportunity to both develop advanced scientific solutions, and drive critical customer and business impacts. 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.You are an individual with outstanding analytical abilities, excellent communication skills, and are 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
- Improve upon existing methodologies by adding new data sources and implementing model enhancements
- Drive scalable solutions
- Drive best practices on the team

- Master's degree in computer science, mathematics, statistics, machine learning or equivalent quantitative field
- Experience building machine learning models or developing algorithms for business application
- Experience programming in Java, C++, Python or related language
- Proficiency in model development, model validation and model implementation.
- Strong programing skills in Python, R or Scala.

- Experience implementing algorithms using both toolkits and self-developed code
- 2+ years of experience of building machine learning models for business application.
- Experience with time series modeling and machine learning forecasting.
- Good knowledge of SQL, Redshift and AWS infrastructure.
- Experience with data management and/or high performance computing.
- Experience working in command-line Linux environments.