AmazonSr. Research Scientist, Amazon Transportation Services (NEST) Science
Amazon is hiring a Sr. Research Scientist, Amazon Transportation Services (NEST) Science in Bellevue, United States. It pays $159k-$215k a year and Level rates it ; you can apply on Amazon.
Level's read on this job
- Level rates this research scientist role Builds AI ●●●●: the job is building AI systems.
- The posting mentions Python, Java and C among its tools and skills.
- Level classes it as a senior role.
- Amazon has 21,000+ other open roles on Level.
- Posted in the last few days.
AI in this role
Design and develop novel mathematical models and machine learning algorithms to optimize Amazon's transportation network.
Come join the Network Engineering, Scheduling and Technology (NEST) Science team within Amazon Transportation Services. We are looking for a Sr. Research Scientist to lead the design and development of novel mathematical models that govern how Amazon's Middle Mile network operates. You will work on scientifically complex, poorly structured problems in network planning, scheduling, and transportation operations, inventing and extending techniques from operations research, machine learning, stochastic modeling, and simulation to solve them. This is a modeling-first role: your primary output is rigorous, original scientific work that reduces transportation cost and improves customer experience at scale.
The ideal candidate has deep expertise in at least one relevant scientific discipline and a track record of taking ambiguous business problems from formulation through to production-grade models. You are comfortable owning the scientific agenda for large problem areas, framing the right questions, inventing solutions where no textbook answer exists, and influencing scientists, engineers, and leaders across multiple teams.
Key job responsibilities
**Invent**
- Invent and design new models and algorithms for scientifically complex problems in transportation network planning, scheduling, equipment selection, and labor optimization
- Frame ambiguous, poorly defined business problems into tractable scientific formulations, distinguishing problems that require novel research from those addressable with existing techniques
- Extend the state of the art in operations research, optimization, machine learning, and stochastic/discrete-event simulation as the problem demands
- Author internal and external peer-reviewed publications where appropriate and not precluded by business considerations
**Implement**
- Lead the design, implementation, and delivery of production-grade models for complex, system-level problems, working from concept through deployment with engineering partners
- Develop code (Python, Java, C++, Julia, or similar) to build, validate, and productionize models at Amazon Code Bar quality where models ship to production
- Build models that are maintainable, extensible, accurate, and cost-effective, making principled trade-offs between scientific rigor and speed of execution
- Design and run experiments and simulations to validate assumptions, quantify benefits, and gate rollouts on solution quality
**Influence**
- Drive the scientific agenda for medium-to-large problem areas, proposing new initiatives and securing leadership buy-in
- Influence science and engineering strategy across multiple teams, building consensus and resolving contentious technical trade-offs
- Mentor and develop other scientists, raise the team's scientific bar, and participate actively in the hiring process
- Communicate complex scientific findings and recommendations clearly to technical and non-technical audiences, including senior leadership
About the team
The Network Engineering, Scheduling, and Technology (NEST) Science Team prototypes, builds, and productionizes mathematical models that reduce transportation cost and improve customer experience in Amazon's Middle Mile network. Equipped with techniques from Operations Research, Machine Learning, and Simulation, these models govern scheduling and equipment selection of hundreds of thousands of truck movements, optimize network configurations, determine transit times between nodes, and simulate network flow under uncertainty for informed decision making. Our core team consists of Applied, Data, and Research Scientists along with technical Product Managers from diverse backgrounds.
Basic qualifications
- 3+ years of investigating the feasibility of applying scientific principles and concepts to business problems and products experience
- PhD, or Master's degree and 5+ years of quantitative field research experience
- Experience with big data technologies such as AWS, Hadoop, Spark, Pig, Hive etc.
- Experience communicating qualitative research methods and findings to non-qualitative researchers
Preferred qualifications
- Experience converting research studies into tangible real-world changes
- Experience with discrete and continuous optimization methodologies and algorithms
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 - 159,200.00 - 215,300.00 USD annually
How we rate this
Sr. Research Scientist, Amazon Transportation Services (NEST) Science 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.
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.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Also common in research scientist jobs at this level
Pay
- This job starts at
- $159k
- Typical research scientist job
- $192k
This posting starts 17% below the typical research scientist job. See research scientist jobs
Questions you could be asked
- Tell me about a project where operations research was part of your work. What did you do?
- 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 optimization was part of your work. What did you do?
- Tell me about a project where stochastic modeling was part of your work. What did you do?
Adapt your resume
- List these exact terms on your resume: Operations Research, Machine learning, Mathematical Modeling, Optimization, and Stochastic Modeling. 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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