Amazon Data Scientist Device Economics Devices Decision Science 

United States, Washington, Seattle 

464641703

In this role, you will support senior leadership decision meetings, approving confidential funding requests (PRFAQs) for brand new devices and services. You will influence build decisions prior to receiving any customer signal. You will leverage science and tools such as conjoint demand models and machine learning models to produce these recommendations. As part of the stakeholder-facing arm of the team, you will own relationships with decision makers to help improve the end-customer experience by making the decisions science-driven. In parallel, you will work with Scientists, Economists, and Product Managers to provide meaningful business solutions and increase the velocity, quality, and scope behind our recommendations.Key job responsibilities
- Design and conduct conjoint analyses to inform decisions across multiple product categories.
- Apply forecasting techniques to predict market trends and product performance across various regions and sales channels (online and offline).
- Develop data augmentation methodologies to enhance the quality and quantity of available data for analysis.
- Analyze complex marketplace dynamics, including new product launches, marketplace expansions, and software improvements, to provide actionable insights.- Produce clear and concise reports and presentations to communicate findings and recommendations to stakeholders at various levels of the organization.- Stay up-to-date with the latest advancements in data science, applied statistics, and machine learning, particularly in the context of consumer electronics.

- 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
- 2+ years of data scientist experience
- 3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience
- Bachelor's degree
- Experience applying theoretical models in an applied environment