Data Scientist II, Device Economics

Amazon; Seattle (WA); On-site; USD 136,000 - 184,000; Full time

Benefits offered by this job

Health insurance

401(k) matching

Paid time off

Job summary

Amazon is seeking a Data Scientist II to join its Device Economics team in Seattle. This position focuses on forecasting for Amazon's innovative device portfolio, requiring expertise in economic modeling, analysis, and strategic thinking.

The ideal candidate will possess a Master's degree in a quantitative field and have 3+ years of relevant experience. Responsibilities include developing forecasts, collaborating with stakeholders, and driving business strategies. The role offers a competitive salary and comprehensive benefits.

Qualifications

• 3+ years of experience in data science or a similar role.
• Experience in statistical modeling and data-driven insights.
• Familiarity with econometrics and demand forecasting.

Responsibilities

• Develop and maintain forecasts for Amazon Devices.
• Explain complex models to non-technical stakeholders.
• Collaborate with teams on strategic planning and forecasting.

Skills

Statistical modeling

Data analysis

Collaboration

Forecasting

Education

Master's degree in a quantitative field

Tools

AWS technologies

Job description

Job ID: 10461434 | Amazon.com Services LLC

We are seeking Data Scientist II with strong science application skills to join our Device Economics team. This role will focus primarily on Amazon's innovative devices and services (e.g. Echo Family of Devices), working at the intersection of economic modeling, forecasting science, and business strategy. The ideal candidate will be responsible for pre-launch forecasts, annualized overall forecasts, identifying substitution patterns, and partnering closely with product managers and marketing managers to understand the evolution of the Devices portfolio.

Key Job Responsibilities

Forecasting & Modeling

1. Develop and maintain pre-launch forecasts and annualized overall forecasts for Amazon Devices.
2. Identify and model substitution patterns across the device portfolio.
3. Build economic and financial models to support demand planning and business decisions.
4. Formulate relevant analytical frameworks to address key economic issues in device forecasting.

Science Communication & Collaboration

1. Explain complex science models and methodologies to non-technical stakeholders including product managers and marketing managers.
2. Collaborate with economists, data scientists, and applied scientists across Decision Science.
3. Present results of analyses to cross-functional teams and leadership.
4. Build trust in science models and forecast outputs with product teams.

Innovation & Strategic Thinking

1. Think creatively about ways that leading‑edge analytics and emerging data sources can address Devices' most pressing business challenges.
2. Help internal teams leverage analytic tools to better manage innovation.
3. Conduct empirical studies and perform quantitative and qualitative research.
4. Identify opportunities to improve forecasting accuracy and business impact.

Cross-Functional Partnership

1. Work closely with product managers and marketing managers to understand portfolio evolution and business strategy.
2. Support DSO leadership in quarterly business reviews and strategic planning.

A Day in the Life

• Split between refining and building models and working with business leaders to interpret them.
• Own science‑based forecasts that can directly impact Amazon's bottom line on the order of multi‑million dollar decisions.
• Perform model refreshes or updates to analyses as needed.
• Develop new techniques to process large data sets, address quantitative problems, and contribute to design of automated systems.

The Decision Science team within DSO (Device Supply Organization) is responsible for forecasting and demand planning initiatives across Amazon Devices. The DSO team of 300+ engineers, scientists, and PMs applies quantitative methods and data-driven approaches to replace judgment-based decisions with science-driven forecasts. Decision Science focuses on lifetime demand forecasting using econometric and machine learning models for rapid reforecasting, mix adjustments, and portfolio management for new product launches. We also inform to go/no-go investment decision for new product initiatives.

Basic Qualifications

• Master's degree in econometrics, statistics, industrial engineering, operations research, optimization, data mining, analytics, or equivalent quantitative field.
• 3+ years of data scientist or similar role involving data extraction, analysis, statistical modeling and communication experience.
• Experience using data and metrics to drive actionable insights at scale.

Preferred Qualifications

• Knowledge of methods for statistical inference (e.g. regression, experimental design, significance testing).
• Experience with AWS technologies.
• Experience with demand forecasting in retail, e‑commerce, or consumer electronics.
• Background in portfolio optimization or product mix analysis.
• Familiarity with substitution modeling and cannibalization analysis.

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.

Base salary ranges:

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

Your Amazon package will include sign‑on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription), Basic Life & AD&D insurance, optional supplemental life plans, Employee Assistance Program, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage, 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.