Amazon Data Scientist II Infra DCPD - PACE 

United States, Washington, Seattle 

555137041

We recently announced that AWS will be water positive by 2030, returning more water to communities than it uses in its direct operations. The company also announced its 2021 global water use efficiency (WUE) metric of 0.25 liters of water per kilowatt-hour, demonstrating AWS’s leadership in water efficiency among cloud providers. To learn more about AWS’s water+ commitment visit: Water Stewardship.Key job responsibilities
As a Data Scientist on the AWS Sustainability team, you will be responsible for developing and implementing machine learning models and statistical analyses to extract insights from large datasets related to sustainability metrics, energy usage, and carbon emissions.Working closely with Software Engineers, Data Engineers, and Product Managers, you will integrate models into production systems and tools. You will identify innovative methodologies that advance our sustainability analytics capabilities. Your role includes optimizing existing models and algorithms to enhance performance, performing ad-hoc analyses to support strategic decisions, and documenting technical approaches.You will stay current with latest developments in data science and sustainability analytics. The role requires strong communication skills to present findings to leadership and cross-functional partners. Throughout all work, you will ensure data quality and integrity through robust validation and testing procedures. This position offers an opportunity to apply data science expertise to meaningful sustainability challenges at global scale.A day in the life

- 2+ years of data scientist experience
- 3+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
- 3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience
- Experience applying theoretical models in an applied environment