Data Scientist II: Shape Long-Term Device Demand

Amazon; Sunnyvale (CA); On-site; USD 157,000 - 213,000; Full time

Job summary

Amazon is seeking a Data Scientist II on the Devices forecasting team to build econometric and machine learning models that project long-term demand and assess feature willingness to pay. You will collaborate with product managers and engineers to shape portfolio decisions and drive insights that influence roadmaps.

You will mentor junior scientists, communicate results through clear visuals and documentation, and contribute to advancing AI-driven analytics within the team.

Qualifications

• 3+ years of data querying languages (e.g. SQL) 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

Responsibilities

• Build and validate econometric and machine learning models that generate long-term demand forecasts for Amazon Devices.
• Assess the incrementality of new products and quantify willingness to pay for product features.
• Collaborate with product managers, engineers, and business stakeholders to scope analytical projects, define metrics, and identify data requirements.
• Communicate findings to technical and non-technical audiences through clear documentation, visualizations, and presentations.
• Mentor less experienced data scientists through code reviews and knowledge sharing.

Skills

SQL

Python

R

Education

Bachelor's degree

Tools

SAS

Matlab

Job description

Amazon is seeking a Data Scientist II on the Devices forecasting team to build econometric and machine learning models that project long-term demand and assess feature willingness to pay. You will collaborate with product managers and engineers to shape portfolio decisions and drive insights that influence roadmaps.

You will mentor junior scientists, communicate results through clear visuals and documentation, and contribute to advancing AI-driven analytics within the team.