Data Scientist II, Long Term Planning and Forecasting
Core
Build scientific tooling and causal inference models to translate long-term forecasts into actionable business intelligence for Amazon's Operations, Stores, and Finance teams.
Role type
Senior IC data scientist (causal inference & forecasting)
Builds
Automated variance decomposition models, causal model libraries, and GenAI-powered narrative generation tools
Domain
Retail operations, long-term strategic planning, econometrics
Deliverable
production ML models
Required skills
causal inference, time-series econometrics, Bayesian methods, automated explainability frameworks, variance bridging, GenAI narrative generation, SQL, Python, statistical modeling
Preferred skills
benchmarking GenAI model performance, defining multi-year program vision, presenting to VP/SVP level leaders
Technologies
Python, SQL, R, SAS, Matlab
Responsibilities
Develop causal inference models and automated explainability frameworks; Build automated Plan-vs-Actual variance decomposition models; Maintain a causal model library with standardized hypothesis pipelines; Develop GenAI-powered narrative generation capabilities; Quantify demand drivers contributing to forecast gaps across revenue, price, units, and inventory metrics
Seniority
Senior, hands-on IC