Data Scientist II, Device Economics

Key job responsibilities

• Forecasting & Modeling
• Develop and maintain pre-launch forecasts and annualized overall forecasts for Amazon Devices
• Identify and model substitution patterns across the device portfolio
• Build economic and financial models to support demand planning and business decisions
• Formulate relevant analytical frameworks to address key economic issues in device forecasting
• Science Communication & Collaboration
• Explain complex science models and methodologies to non-technical stakeholders including product managers and marketing managers
• Collaborate with economists, data scientists, and applied scientists across Decision Science
• Present results of analyses to cross-functional teams and leadership
• Build trust in science models and forecast outputs with product teams
• Innovation & Strategic Thinking
• Think creatively about ways that leading-edge analytics and emerging data sources can address Devices' most pressing business challenges
• Help internal teams leverage analytic tools to better manage innovation
• Conduct empirical studies and perform quantitative and qualitative research
• Identify opportunities to improve forecasting accuracy and business impact
• Cross-Functional Partnership
• Work closely with product managers and marketing managers to understand portfolio evolution and business strategy
• Support DSO leadership in quarterly business reviews and strategic planning

About the team

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