Data Scientist: Forecasting & Optimization for Capacity

Amazon Inc.; Seattle (WA); On-site; USD 136,000 - 184,000; Full time

Benefits offered by this job

Health insurance

401(k) matching

RSU program

Parental leave

Job summary

Amazon.com Services LLC, within the CloudTune forecasting team, seeks a Data Scientist to develop ML models for multi-year capacity demand forecasting and optimization of AWS capacity planning. You will work with scientists, software engineers, data engineers, and PMs on stochastic optimization, time series modeling, and operations research to manage uncertainty and scale infrastructure decisions.

The role emphasizes data processing, model development, documentation, and communication of results

Qualifications

• 2+ years of data scientist experience.
• 3+ years of SQL, Python or R/SAS/MATLAB experience.
• 3+ years of ML/statistical modeling data analysis tools and techniques.
• 1+ years of working with or evaluating AI systems.
• Experience applying quantitative analysis to business problems and data-driven decisions.
• Currently pursuing or holding a Master’s degree or higher in STEM.

Responsibilities

• Process and analyze large data sets; mine additional data sources as needed.
• Build statistical models and scalable solutions for multi-year capacity demand forecasting.
• Create, enhance, and maintain technical documentation and present to scientists and leaders.
• Analyze large-scale operational data to identify patterns and inform model development.
• Present research findings to scientists, engineering teams, and senior leadership.

Skills

Data science

SQL

Python

R

Education

Master’s degree in STEM

PhD in STEM

Tools

SAS

MATLAB

Job description

Amazon.com Services LLC, within the CloudTune forecasting team, seeks a Data Scientist to develop ML models for multi-year capacity demand forecasting and optimization of AWS capacity planning. You will work with scientists, software engineers, data engineers, and PMs on stochastic optimization, time series modeling, and operations research to manage uncertainty and scale infrastructure decisions.

The role emphasizes data processing, model development, documentation, and communication of results