Data Scientist

Who you are

• 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
• Experience in Python, Perl, or another scripting language
• Experience in a ML or data scientist role with a large technology company

What the job involves

• As a Data Scientist II on our Devices forecasting team, you will answer that question by building econometric and machine learning models that project long-term demand, assess the incrementality of new products, and quantify willingness to pay for specific features
• Your analysis will directly shape portfolio decisions, helping product managers decide what to build next. This is a team that is investing in AI to accelerate how science informs business strategy, making now a particularly exciting time to join
• Build and validate econometric and machine learning models that generate long-term demand forecasts for Amazon Devices, selecting the right methodology based on data characteristics and business context
• Assess the incrementality of new products and quantify willingness to pay for product features, translating model outputs into clear narratives that help product managers adjust their portfolio strategy
• Collaborate with product managers, engineers, and business stakeholders to scope analytical projects, define metrics, and identify the data requirements needed to answer ambiguous forecasting questions
• Communicate findings to technical and non-technical audiences through clear documentation, effective visualizations, and well-structured presentations that drive informed decisions
• Mentor less experienced data scientists through code reviews, knowledge sharing, and active participation in scientific discussions and team planning
• You might spend your morning refining a demand forecast model, testing how a new product feature variable improves prediction accuracy
• After lunch, you could be walking product managers through your incrementality analysis and aligning on what the numbers mean for their roadmap
• Later, you might review a teammate's willingness-to-pay study or experiment with an AI-based approach to accelerate your modeling pipeline. Your work moves between deep independent analysis and collaborative sessions where you translate complex results into actionable recommendations
• Our team owns long-term forecasting and product analytics for Amazon Devices. We build the science that tells the story of where customer demand is headed and what drives it
• You will work alongside scientists, engineers, and product managers who value rigorous analysis and practical impact
• We are currently expanding our use of AI to accelerate how we deliver insights, and we are looking for people who are curious, collaborative, and ready to help shape that direction