Forecasting & Optimization Research Scientist

Amazon; Omaha, Northern (NE, KY); Hybrid; USD 126,000 - 170,000; Full time

Job summary

Amazon’s CloudTune team seeks a Research Scientist to advance capacity planning through machine learning-based forecasting and optimization on massive datasets. You will collaborate with scientists, software engineers, data engineers, and product managers to tackle stochastic optimization and time series challenges that drive multi-million dollar decisions.

The role emphasizes developing demand models, allocating resources, and balancing cost with service levels across global infrastructure.

Qualifications

• PhD in a quantitative field or MS with 1+ years of quantitative research experience.
• Experience applying scientific principles to business problems.
• Experience with data analysis packages (R, SAS, MATLAB, etc.).
• Experience using SQL databases to manage and analyze large data sets.

Responsibilities

• Formulate capacity planning and resource allocation as mathematical optimization problems (linear programming, stochastic optimization, MILP).
• Develop demand forecasting models using machine learning with risk-aware loss functions.
• Design and implement safety stock and retention policy optimization frameworks balancing costs vs fulfillment risk.
• Process and analyze large-scale operational data to identify patterns and inform model development.
• Create, enhance, and maintain technical documentation and present findings to scientists and leadership.

Skills

Data analysis

Quantitative research

Forecasting techniques

Education

PhD in a quantitative field

MS degree + 1+ years experience

Tools

R

SAS

MATLAB

SQL

Job description

Amazon’s CloudTune team seeks a Research Scientist to advance capacity planning through machine learning-based forecasting and optimization on massive datasets. You will collaborate with scientists, software engineers, data engineers, and product managers to tackle stochastic optimization and time series challenges that drive multi-million dollar decisions.

The role emphasizes developing demand models, allocating resources, and balancing cost with service levels across global infrastructure.