Applied Scientist, AWS Insights & Optimization

Amazon is hiring an Applied Scientist, AWS Insights & Optimization in Seattle, United States. It pays $143k-$193k a year and Level rates it ; you can apply on Amazon.

Level's read on this job

Level rates this applied scientist role Builds AI ●●●●: the job is building AI systems.
Tools and skills the posting cites include Python, Java and C.
Level classifies it as a senior role.
Level lists 20,000+ other open roles at Amazon.

AI in this role

Design and build AI/ML models, forecasting engines, and LLM evaluation science for AWS cloud financial management.

pythonjavac

ai-evaluationmachine-learningmathematical-modelingtime-series-forecastingllm-evaluationalgorithms

AWS Insights & Optimization is looking for an Applied Scientist to help develop sophisticated algorithms and models that involve analyzing and learning from over 540 billion customer cost, usage, and utilization events daily. We use this data to power cost anomaly detection, cost forecasting, rightsizing recommendations across seven compute services, Savings Plans optimization, and AI-powered conversational experiences that help customers understand and optimize their AWS spend. Our team's vision is to be the world's provider of intelligent AWS cloud financial management, where customers can understand, control, and optimize usage of AWS products. We sit at the nexus of all AWS services and interact directly with end-customers, building relationships with teams across AWS to ensure we offer a secure and reliable experience that builds trust and provides intelligent insights.

As a successful Applied Scientist in AWS Insights & Optimization, you will own models end-to-end — from problem formulation through experimentation to production deployment. Your work may span cost anomaly detection (decomposition, detection, and root cause attribution), time-series forecasting with a focus on accuracy and consistency, rightsizing engines for EC2, EBS, Lambda, ECS, RDS, and Aurora, LLM evaluation science for AI-powered agent experiences, or agent memory architectures that enable persistent, adaptive behavior across sessions. You will work closely with applied scientists, software engineers, and product teams to enhance existing models and build new ones that solve challenging customer problems. You will drive implementation of proposed models, establish testing strategies to validate them before and after production, and define evaluation metrics that determine whether capabilities meet the quality bar. We value accuracy over speed, measurability over intuition, and simplicity over complexity — the simplest model that meets the bar wins. You are an analytical problem solver who enjoys diving into data, are excited about investigating and developing algorithms, and can influence technical teams and business stakeholders to solve real-world customer problems.

Basic qualifications

- 3+ years of building models for business application experience
- PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience
- Experience in patents or publications at top-tier peer-reviewed conferences or journals
- Experience programming in Java, C++, Python or related language
- Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing

Preferred qualifications

- Experience using Unix/Linux
- Experience in professional software development

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 - 142,800.00 - 193,200.00 USD annually

How we rate this

Applied Scientist, AWS Insights & Optimization at Amazon rates 85 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

●●●● Builds AI80 to 100
●●●○ Works on AI60 to 79
●●○○ Uses AI40 to 59
●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Key facts

Applied Scientist, AWS Insights & Optimization is an open job at Amazon.
Level rates this role AI Level 4 of 4: Builds AI.
The listed salary is $143k-$193k a year.
The role is based in US, WA, Seattle.
The job was posted on May 9, 2026.
Seniority: senior.
Applications are handled by Amazon. Apply on Amazon

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

AI EvaluationMachine learningMathematical ModelingTime Series ForecastingLLM EvaluationAlgorithmsPythonJava

Also common in applied scientist jobs at this level

Machine learning Deep learning Generative AI NLP Reinforcement learning TensorFlow

Pay

This job starts at: $143k
Typical applied scientist job: $172k

This posting starts 17% below the typical applied scientist job. See applied scientist jobs

Questions you could be asked

How do you decide that one model's output is better than another's for a given task?
Tell me about a project where machine learning was part of your work. What did you do?
Tell me about a project where mathematical modeling was part of your work. What did you do?
Tell me about a project where time series forecasting was part of your work. What did you do?
Tell me about a project where llm evaluation was part of your work. What did you do?

Adapt your resume

List these exact terms on your resume: AI Evaluation, Machine learning, Mathematical Modeling, Time Series Forecasting, and LLM Evaluation. An applicant tracking system matches the wording, not the idea.
Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.

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