Data Scientist II - Long-Term Forecasting & Planning

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

Job summary

Amazon is seeking an experienced Data Scientist to drive scientific tooling for how business customers interact with LTPF forecasts and plans. You will lead cross-functional programs spanning Operations, Stores, and Finance to translate forecasts into actionable business insights across a multi-year roadmap.

You will build causal inference models, explainability tools, and GenAI-powered narratives to support decision-making at VP-level planning reviews, while guiding a team of researchers and

Qualifications

• 2+ years of data scientist experience.
• 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.
• 3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience.
• 1+ years of guiding and coaching a group of researchers experience.
• 1+ years of working with or evaluating AI systems experience.
• 1+ years of creating or contributing to mathematical textbooks, research papers, or educational content experience.
• Master's degree in Science, Technology, Engineering, or Mathematics (STEM), or experience working in Science, Technology, Engineering, or Mathematics (STEM).
• Experience applying theoretical models in an applied environment.

Responsibilities

• You will develop causal inference models, automated explainability frameworks, and variance bridging methodologies that translate LTPF's forecasts and plans into actionable business intelligence.
• Your work will enable leadership to understand why forecasts and actuals diverge, what is driving demand shifts, and how strategic decisions propagate through the planning ecosystem.
• You will build automated Plan-vs-Actual and Actual-vs-Actual variance decomposition models that quantify the contribution of individual demand drivers to observed gaps across revenue, price, units, inventory, and capacity metrics at multiple granularities to serve audiences from working-level analysts to VP-level planning reviews cycles.
• You will build and maintain a causal model library with standardized hypothesis generation and validation pipelines, applying techniques from causal inference, time-series econometrics, and Bayesian methods. Each model will include calibrated confidence scoring and reusable components that scale across worldwide marketplaces.
• You will develop GenAI-powered narrative generation capabilities that synthesize quantitative variance outputs into human-readable performance summaries and design automated hypothesis ranking to determine which demand drivers are most responsible for observed forecast error.

Skills

Data science

Python

SQL

Statistics

Causal inference

Communication

Education

Master's degree in STEM

Tools

Python

SQL

R

Job description

Amazon is seeking an experienced Data Scientist to drive scientific tooling for how business customers interact with LTPF forecasts and plans. You will lead cross-functional programs spanning Operations, Stores, and Finance to translate forecasts into actionable business insights across a multi-year roadmap.

You will build causal inference models, explainability tools, and GenAI-powered narratives to support decision-making at VP-level planning reviews, while guiding a team of researchers and