Data Scientist II, Data Scientist, Decision Science

DataJobs; Sunnyvale (CA); On-site; USD 136,000 - 213,000; Full time

Benefits offered by this job

Sign-on payments

RSUs

Health insurance

401(k) matching

Paid time off

Parental leave

Job summary

Amazon Devices in Sunnyvale, CA is seeking a Data Scientist II to build econometric and machine learning models for long-term demand forecasting and product insights.

You will collaborate with product managers and engineers, quantify incrementality and willingness to pay, and translate results into actionable guidance.

Mentor junior data scientists, contribute to forecasting roadmaps, and communicate findings clearly to both technical and non-technical stakeholders.

Qualifications

• 3+ years of experience with SQL, Python, or statistical software.
• 2+ years of data scientist experience.
• 3+ years of ML and statistical modeling experience.
• Bachelor’s degree.

Responsibilities

• Build and validate econometric and machine learning models for long-term demand forecasting.
• Evaluate incrementality of new products and willingness to pay for features.
• Partner with product managers, engineers and stakeholders to scope projects and define metrics.
• Share findings with technical and non-technical audiences using docs and visuals.
• Mentor less experienced data scientists through code reviews and knowledge sharing.

Skills

SQL

Python

Statistics

Data analysis

Education

Bachelor’s degree

Tools

R

SAS

Matlab

Perl

Job description

Amazon Devices is building the analysis that guides long-term portfolio decisions, turning customer demand signals into actionable forecasts and product insights. In this Data Scientist II role, you will develop econometric and machine learning models to predict long-term demand, evaluate incrementality for new products, and estimate willingness to pay for feature sets. You will collaborate closely with product and engineering partners and translate model outputs into clear guidance for technical and non-technical stakeholders.

What you’ll do

• Build and validate econometric and machine learning models for long-term demand forecasting for Amazon Devices, choosing methods based on data characteristics and business context.
• Evaluate incrementality of new products and quantify willingness to pay for product features, converting results into narratives that support portfolio strategy updates.
• Partner with product managers, engineers, and business stakeholders to scope analytical projects, define metrics, and identify data needs for forecasting questions.
• Share findings with both technical and non-technical audiences using documentation, visualizations, and presentations that enable informed decisions.
• Mentor less experienced data scientists through code reviews, knowledge sharing, and participation in scientific discussions and team planning.

Required qualifications

• 3+ years of experience with data querying languages (e.g., SQL), scripting languages (e.g., Python), and/or statistical or mathematical software (e.g., R, SAS, Matlab, etc.).
• 2+ years of data scientist experience.
• 3+ years of experience with machine learning and statistical modeling analysis tools and techniques, including parameters that influence performance.
• Bachelor’s degree.
• Experience applying theoretical models in an applied environment.

Technologies

• SQL
• Python
• R
• SAS
• Matlab
• Perl

Preferred qualifications

• Experience in Python, Perl, or another scripting language.
• Experience in a machine learning or data scientist role at a large technology company.

Compensation and location

• Location: Sunnyvale, CA (onsite)
• Salary: USD 136,000 - 212,800 per year

Benefits

• Sign-on payments
• Restricted stock units (RSUs)
• Health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and 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

A day in the life

• Refine a demand forecast model and test how adding a new product feature variable changes prediction accuracy.
• Walk product managers through incrementality analysis and align on what the results mean for roadmap planning.
• Review a willingness-to-pay study or experiment that uses an AI-based approach to accelerate the modeling pipeline.
• Alternate between deep independent analysis and collaborative sessions focused on turning complex findings into recommendations.

The team owns long-term forecasting and product analytics for Amazon Devices, building the science behind where customer demand is headed and what influences it most. You will work alongside scientists, engineers, and product managers who value rigorous analysis with practical impact as the team expands its use of AI to deliver insights faster.