Role Overview
Amazon is hiring a mid-level Research Scientist, Operational Efficiency, AET Planning and Analytics Science. This is a full-time role in Arlington. Part of Amazon's Data Science hiring, posted today. applications are still in the early window, before most candidates have applied. Full responsibilities, required qualifications, and the apply link are listed in the description below.
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Job Description
Description
We're looking for a Research Scientist to join a team that builds the science behind how Amazon supports its 1.5M+ employees - from forecasting demand across HR services to optimizing how work gets routed and assigned in real time. You'll own high-impact operations research and causal inference work that directly reduces costs and improves the employee experience at global scale.
In This Role, You Will
- Design and build simulation and optimization models that automate workforce scheduling, hiring, and task assignment across Amazon's HR contact centers and back-office operations
- Develop causal inference frameworks to measure the true impact of policy changes, product launches, and AI-driven initiatives on employee experience and operational efficiency
- Collaborate with senior leaders to translate complex analytical findings into actionable strategies that influence staffing, routing, and resource allocation decisions affecting thousands of associates
- Push the boundaries of what's possible by combining operations research with machine learning and generative AI to solve novel workforce optimization problems
This isn't a role where you'll be running standard analyses on repeat. You'll be building novel solutions - like contact center simulators that replicate real-world operations, scheduling optimizers that replace manual processes, and experiment frameworks that credibly quantify the impact of large-scale organizational changes. Your work will directly inform decisions made by VP and Director-level leaders who set the strategy for how Amazon supports its employees at scale.
About The Team
We are a team of economists, research scientists, and data scientists within Amazon's People Experience and Technology Finance organization. Our mission is to make Amazon's employee support services smarter, faster, and more efficient through rigorous science - from forecasting models that drive hiring plans to simulation engines that optimize how HR services are delivered to Amazon's global workforce of 1.5M+ people.
Our work runs in production, informs weekly planning decisions, and shapes resource allocation at scale. We value intellectual rigor, ownership, and collaboration — publishing at internal science conferences, maintaining shared codebases, and holding each other to high technical standards. You'll have real ownership from day one: framing problems, building solutions, and presenting results to senior leaders who act on your recommendations.
Basic Qualifications
- PhD, or Master's degree and 4+ years of quantitative field research experience
- Experience with statistical modeling / machine learning
- Knowledge of R, MATLAB, Python or similar scripting language
Preferred Qualifications
- Experience investigating the feasibility of applying scientific principles and concepts to business problems and products
- Experience in causal modeling like graphical models, causal Bayesian network, potential outcomes, A/B testing, experiments, quasi-experiments, and data science workflows
- Experience consulting with senior leadership and executives in a fast-paced environment
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, VA, Arlington - 136,000.00 - 184,000.00 USD annually
USA, WA, Bellevue - 136,000.00 - 184,000.00 USD annually
USA, WA, Seattle - 136,000.00 - 184,000.00 USD annually
Company - Amazon.com Services LLC
Job ID: A10447029
Frequently Asked Questions
How do I apply for the Research Scientist, Operational Efficiency, AET Planning and Analytics Science position at Amazon?
Use the Apply button above to submit your application directly to Amazon. Most applications take less than 5 minutes if your resume and contact details are ready, and you'll be routed to the employer's official application system to finish.
Where is the Research Scientist, Operational Efficiency, AET Planning and Analytics Science position at Amazon located?
This position is based in Arlington. Amazon has not indicated remote or hybrid options for this role, so candidates should plan for on-site work.
What does a Research Scientist, Operational Efficiency, AET Planning and Analytics Science at Amazon earn?
Amazon has not disclosed a salary range in this posting. Many employers share specifics later in the interview process; you can also ask during a recruiter screen if compensation transparency is important to you.
When was the Research Scientist, Operational Efficiency, AET Planning and Analytics Science role at Amazon posted?
This role was posted on June 12, 2026 (today). It's still listed as actively hiring; we re-confirm openings against the source system multiple times per day and remove closed roles.
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