Data Scientist II, Data Scientist, Decision Science

About the role

What will customers want from Amazon Devices one, two, or three years from now? 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.

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.

Responsibilities

• 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.

Requirements

• 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

Qualifications

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

Skills

• Data querying languages (SQL)
• Scripting languages (Python, Perl)
• Statistical/mathematical software (R, SAS, Matlab)
• Machine learning and statistical modeling
• Data analysis tools and techniques

Benefits

• Sign-on payments and restricted stock units (RSUs)
• Comprehensive health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance, option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage)
• 401(k) matching
• Paid time off
• Parental leave

Pay

• USA, CA, Sunnyvale: $157,300.00 - $212,800.00 USD annually
• USA, WA, Seattle: $136,000.00 - $184,000.00 USD annually