Data Scientist , Demand Forecasting

Position: Data Scientist I, Demand Forecasting
Description

Amazon has the world's most complex supply chain: we fulfill global demand for hundreds of millions of products at lightning fast delivery speeds. We need your skills to optimize our supply chain, with the end goal of delighting our customers. A core part of the supply chain operations is Demand Forecasting:
We forecast the demand of tens of millions of products. These forecasts are used to make many decisions, such as automatically order hundreds of millions worth of inventory, decide where to place that inventory, and establish labor plans for hundreds of warehouses.

The Product Data Science team within Forecasting & Labs (part of Supply Chain Optimization Technologies) is looking for an analytical and technically skilled Data Scientist to join our team. Our team is responsible for bias correction model development and A/B testing for forecast improvements, GenAI/LLM research for forecast explainability, and deep analytics for Labs and Foundation Models. We work horizontally across the forecasting product portfolio-including National, Regional, Grocery, SSD, Inbound, and CIV forecasting-to embed advanced analytics and machine learning solutions where they create the most value.

This position will be responsible for developing and supporting data science methodologies and building models to address ambiguous forecasting questions. The Data Scientist will design and analyze experiments (A/B tests) to measure the impact of forecast model changes, develop bias correction models to improve forecast accuracy, and contribute to GenAI/LLM-based approaches for forecast explainability and interpretability. The role also involves supporting the Labs experimentation platform, which designs and executes inference and experimentation systems that measure the impact of initiatives across SCOT.

The Data Scientist needs to be familiar with deriving causal inferences using observational and experimental data and able to model variations related to demand prediction, out of stock, seasonality, and different lead times and spans.

This role requires an individual with excellent analytical abilities as well as business acumen. The successful candidate will be a self-starter comfortable with ambiguity, with attention to detail, vocally self-critical, and an ability to work in a fast-paced and ever-changing environment. They recognize that the true measure of the success of the work product is based on the business impact the findings have had.

The Demand Forecasting Team is looking for an analytical and technically skilled Data Scientist to join our team. This position will be responsible for developing and supporting best-in-class data science methodologies and building models to address ambiguous forecasting questions. The Data Scientist needs to be familiar with deriving causal inferences using observational data and able to model variations related with demand prediction, out of stock, seasonality, and different lead times and spans.

Upon completion of statistical analysis, the Data Scientist needs to communicate measurement results to stakeholders by translating technical framework to business-oriented insights.

This role requires an individual with excellent analytical abilities as well as business acumen. The successful candidate will be a self-starter comfortable with ambiguity, with attention to detail, vocally self-critical, an ability to work in a fast-paced and ever-changing environment. They recognize that the true measure of the success of the work product is based on the business impact the findings have had.

Key job responsibilities

- Design and analyze experiments (A/B tests) to measure the impact of forecast model changes and SCOT initiatives, drawing causal inferences from both experimental and observational data

- Develop bias correction models to improve forecast accuracy across Amazon's demand forecasting systems, including National, Regional, Grocery, SSD, Inbound, and CIV forecasts

- Contribute to GenAI/LLM-based research for forecast explainability and interpretability, helping stakeholders understand what drives forecast signals

- Support and enhance the Labs experimentation platform by building scalable inference and measurement solutions that quantify the impact of forecasting improvements

- Work horizontally across the forecasting product portfolio and collaborate with product managers, applied scientists, and engineering teams to embed analytics and ML solutions where they create the most value

- Use large datasets to build models addressing ambiguous forecasting questions, including demand prediction, out of stock, seasonality, and varying lead times and spans

- Interpret data, write reports, and communicate measurement results to stakeholders by translating technical frameworks into business-oriented insights and actionable recommendations

- Keys to success in this role include exceptional analytics, statistics, judgment, and communication skills. The candidate will need to be able to extract…