Data Scientist, CloudTune
Company websiteamazon.com (Amazon, opens in new tab)
Base salary $136K to $184K
Employer-published annual base salary, USD. Advertised base range in Seattle, WA
You apply on the employer's own site. Six Figure Work does not handle applications.
- LocationSeattle, WA
- WorkplaceWorkplace not stated
- Status at last checkSource accepting applications when checked
- Last checked (32 min ago) · observed since
About this job
Amazon's eCommerce Foundation (eCF) organization provides the core technologies that drive and power Amazon's Stores, Digital, and Other (SDO) businesses. Millions of customer page views and orders per day are enabled by the systems eCF builds from the ground up. CloudTune, within eCF, empowers growth and business agility needs by automatically and efficiently managing AWS capacity and business processes needed to safely meet Amazon's customer demand. CloudTune serves its primary customers, internal software teams, through forecast-driven automation of cost controllership, capacity management, and scaling. We predict expected load, and drive procurement and allocation of AWS capacity for new product launches and high-velocity events like Prime Day and Cyber Monday.
CloudTune is looking for a Data Scientist to join our forecasting and optimization team. The team develops sophisticated algorithms that combine machine learning-based demand forecasting with mathematical optimization to solve large-scale capacity planning problems under uncertainty. We work with massive datasets — spanning thousands of availability zone and instance family combinations across global regions — to determine optimal resource allocation strategies that balance infrastructure holding costs against service availability requirements. These models directly inform multi-million dollar capacity investment decisions and drive automated procurement, retention, and release policies across Amazon's compute infrastructure.
As a Data Scientist in CloudTune, you will work with other scientists, software engineers, data engineers, and product managers on a variety of important research problems in the areas of stochastic optimization, time series modeling, and operations research. You will work on statistical problems with a high level of ambiguity. You will analyze and process large amounts of data, develop new algorithms and improve existing approaches based on statistical models, machine learning algorithms and big data solutions to automatically scale Amazon’s compute infrastructure, optimizing the balance between availability risk and cost efficiency for all of Amazon businesses.
Key job responsibilities
- Process and analyze large data sets, mining additional data sources as needed
- Build statistical models and drive scalable solutions for multi-year capacity demand forecasting horizons
- Create, enhance, and maintain technical documentation, and present to other scientists and business leaders
- Process and analyze large-scale operational data to identify patterns and inform model development
- Create, enhance, and maintain technical documentation, and present research findings to scientists, engineering teams, and senior leadership
Basic 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 working with or evaluating AI systems experience
- Experience applying quantitative analysis to solve business problems and making data-driven business decisions
- Knowledge of machine learning concepts and their application to reasoning and problem-solving
- Currently has, or is in the process of obtaining, a Master's degree or above in Science, Technology, Engineering, or Mathematics (STEM)
Preferred Qualifications
- Ph.D. in Science, Technology, Engineering, or Mathematics (STEM)
- Experience in a ML or data scientist role with a large technology company
- Experience in defining and creating benchmarks for assessing GenAI model performance
- Experience effectively communicating complex concepts through written and verbal communication
- Knowledge of relevant statistical measures such as confidence intervals, significance of error measurements, development and evaluation data sets, etc.
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.
The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.
USA, WA, Seattle - 136,000.00 - 184,000.00 USD annually
Source: Amazon · View original posting (opens in new tab)
Pay in context
This role's base floor ($136,000) is above 18% of the 324 Data & ML roles in Washington listed on this site; 21 others list the same floor. Their median floor is $143,700; the middle half runs from $136,000 to $168,025.
Only jobs on this site count, and each one publishes a base salary of $100,000 or more, so this compares six-figure jobs with each other, not with the whole market. Computed Nov 6, 2026.
This listingData Scientist, CloudTune$136K to $184K
Sr. Product Manager, Legal Technology$136,000 to $184,100
Research Scientist, WW Sustainability$136K to $184K
Power Engineer, Rack Power$136K to $184K
Security Engineer, Platform Security$136K to $184K
Product Manager III, Cross Border Team$136,000 to $184,100
Data Scientist II, AWS Managed Operations Intelligence (MOI) - Data Science$136K to $184K
Chart as a table
| Role | Published base |
|---|---|
| Data Scientist, CloudTune (this listing) | $136K - $184K |
| Sr. Product Manager, Legal Technology | $136,000 - $184,100 |
| Research Scientist, WW Sustainability | $136K - $184K |
| Power Engineer, Rack Power | $136K - $184K |
| Security Engineer, Platform Security | $136K - $184K |
| Product Manager III, Cross Border Team | $136,000 - $184,100 |
| Data Scientist II, AWS Managed Operations Intelligence (MOI) - Data Science | $136K - $184K |
Observed changes
- Began meeting the published-salary criteria
- First observed on the employer's board
- Observed since
- Employer-stated posting date
- 2026-10-20
Where this pay comes from
Location as the employer wrote it: US, WA, Seattle
USA, WA, Seattle - 136,000.00 - 184,000.00 USD annually
- Method
- Employer text, read with fixed rules and re-verified
- Checked
- Rule set
- us-base-v2
The pay passage appears in the employer's own job text. Fixed, deterministic rules located it, and the passage below was checked against the stored copy of the posting.
What we verified
- The pay figures come from the employer's own listing, quoted exactly above.
- The pay is an annual base salary in US dollars with a minimum of at least $100,000.
- The role was publicly listed on the employer's job board when last checked.
We do not verify what the employer will actually offer, whether the employer is still recruiting for the role, or anything beyond what the employer published. Full methodology.
