Applied Scientist, Selection And Inventory Science

AI in this role

Develop advanced machine learning models and reinforcement learning foundation models for supply chain optimization.

pythonjavac

machine-learningreinforcement-learningcausal-inferenceoperations-researchdeep-learning

As an Applied Scientist, you will work on high-impact, real-world problems in product selection and inventory management using techniques from operations research, causal inference, forecasting, reinforcement learning and agentic artificial intelligence. You will develop state-of-the-art solutions to optimize customer experience with supply chain levers. You will partner closely with engineering and business teams to turn these models into trusted, scalable decisions. You will publish your work in top conferences and journals.

Key job responsibilities
- Develop stochastic and multi-objective optimization models for assortment planning.
- Apply causal inference and forecasting to measure impact and inform decisions.
- Build reinforcement learning foundation models for large-scale sequential decision making in inventory management.
- Translate rigorous science into clear, actionable recommendations, and communicate them to stakeholders.

Basic qualifications

- PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience
- 3+ years of building models for business application 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 in state-of-the-art deep learning models architecture design and deep learning training and optimization and model pruning
- Experience in designing experiments and statistical analysis of results
- 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, Bellevue - 142,800.00 - 193,200.00 USD annually

How we rate this

Applied Scientist, Selection And Inventory Science at Amazon rates 90 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. Open the description and count.

Prepare for this job

A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.

Skills and AI tools this role asks for

Machine LearningReinforcement LearningCausal InferenceOperations ResearchDeep LearningPythonJavaC

Questions you could be asked

Tell me about a project where machine learning was part of your work. What did you do?
Tell me about a project where reinforcement learning was part of your work. What did you do?
Tell me about a project where causal inference was part of your work. What did you do?
Tell me about a project where operations research was part of your work. What did you do?
Tell me about a project where deep learning was part of your work. What did you do?

Adapt your resume

List these exact terms on your resume: Machine Learning, Reinforcement Learning, Causal Inference, Operations Research, and Deep Learning. 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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