Amazon Systems Development Engineer OTS - Global Portfolio Strategy 

United States, Texas, Austin 

878338659

Key job responsibilities
• Own the design, development, and maintenance of scalable solutions for analyses and models.
• Create innovative, sophisticated analytic models to address critical issues but also meet key business criteria (cost/risk/business impact) and key technical criteria (reliability/validity/predictability)
• Lead technical aspects of experiment design in collaboration with the greater ER team.
• Find and create ways to measure the workforce experience at multiple levels in the organization.
• Identify and advocate for technical options related to machine learning, data mining, and other statistical approaches
• Document feasibility requirements, code comments and other technical documentation required to transfer knowledge to other technical staff and management
• Write queries and have in-depth knowledge of the data available in area of responsibility.
• Troubleshoot operational data-quality issues and review/audit existing ETL jobs and queries.
• Collaborate on developing effective Dashboards to surface insights to senior leadership
• Communicate pros and cons of analytic frameworks to the development team
• Uncover drivers, impacts, and key influences on productivity and innovation outcomes
• Develop predictive and optimization models for key applications
• Navigate a variety of data sources, such as open text comments, survey results and free text fields inputs
• Ability to work in a highly collaborative environment with peers that have a range of technical aptitudes
• Maintain an understanding of the latest trends in data science and machine learning
• Recommend improvements to back-end data sources for increased accuracy and simplicity.

- 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