Amazon Data Scientist II Support Products & Services 

United States, Washington, Seattle 

501201726

SP&S's key to success is the diverse set of skills and experiences on our team. Operations, program, analytics, science, and engineering roles come together to innovate in magical ways. As an employee, you will have a myriad of growth and career opportunities.
Key job responsibilities
• Implement statistical methods to solve specific business problems utilizing code (Python, R, Scala, etc.).
• Drive design and development of user classification models and other predictive models to enable a personalized experience for a user.
• Improve upon existing methodologies by developing new data sources, testing model enhancements, and fine-tuning model parameters.
• Collaborate with program management, product management, applied science, software developers, data engineering, and business leaders to provide science support, and communicate feedback; develop, test and deploy a wide range of statistical, econometric, and machine learning models.
• Build customer-facing reporting tools to provide insights and metrics which track model performance and explain variance.
• Communicate verbally and in writing to business customers with various levels of technical knowledge, educating them about our solutions, as well as sharing insights and recommendations.
• Earn the trust of your customers by continuing to constantly obsess over their needs and helping them solve their problems by leveraging technology
Seattle, WA, USA

- Master's degree in a quantitative field, or Bachelor's degree and 5+ years of a quantitative field such as statistics, mathematics, data science, business analytics, economics, finance, engineering, or computer science experience
- 2+ years of data scientist experience involving data extraction, analysis, statistical modeling
- 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

- Master's degree in a quantitative field
- Knowledge of relevant statistical measures such as confidence intervals, significance of error measurements, development and evaluation data sets, etc.