AmazonApplied Scientist - Machine Learning, Amazon Transportation
Amazon is hiring an Applied Scientist - Machine Learning, Amazon Transportation in Bellevue, United States. It pays $143k-$193k a year and Level rates it ; you can apply on Amazon.
Level's read on this job
- Builds AI ●●●● is how Level rates this applied scientist role: the job is building AI systems.
- Tools and skills the posting cites include Python, GenAI and machine learning.
- Level classifies it as a mid-level role.
- Level lists 20,000+ other open roles at Amazon.
AI in this role
Invent and build machine learning models and algorithms to optimize Amazon's middle mile transportation network.
Amazon's transportation network moves millions of truckloads of freight between vendors, warehouses, and customers using a fleet of trucks, trains, and airplanes, on time and at low cost. Operating it requires constant decisions about how to route, schedule, and balance capacity across the network, and our strategy is to make those decisions with science-driven technology. Because existing techniques rarely fit Amazon's scale and unique business needs, this role centers on inventing new approaches and algorithms.
As an Applied Scientist, you'll develop machine learning, forecasting, and prediction models and algorithms. You role will initially develop transit time prediction and uncertainty models. Your models will impact business decisions worth billions of dollars and improve the delivery experience for millions of customers.
Key job responsibilities
- Design and develop machine learning, forecasting, and other prediction models that enhance our optimization and planning systems.
- Build models and algorithms from prototype to production-level systems.
- Translate ambiguous business problems into modeling approaches, and drive the technical design with product, engineering, and operations partners.
- Influence key business decisions through rigorous modeling and analysis.
- Communicate results and recommendations to scientific and business audiences.
A day in the life
- Analyze data to investigate a business problem or model performance and identify improvements
- Brainstorm new algorithmic strategies or business opportunities with fellow scientists
- Leverage GenAI to build and test your new model features
- Run a simulation or experiment to evaluate your model’s performance
- Meet with product and tech partners to review project requirements, data, design, or other project decisions
- Review code changes or a design document from a fellow scientist or engineers
- Write and present a paper documenting algorithm features, results, and recommendations
About the team
Middle Mile Surface Research Science builds the models and algorithms that plan and operate Amazon's middle mile network. Our work spans operations research, optimization, and machine learning. We work on vehicle route planning, capacity planning, scheduling, network design, transit-time prediction, demand forecasting, and equipment re-balancing. Our team of about ten scientists is part of a broader science organization whose scientists bring deep expertise in machine learning and optimization. We optimize decisions worth billions of dollars and reach millions of customers.
Basic qualifications
- PhD, or Master's degree and 4+ years of science, technology, engineering or related field experience
- Experience building machine learning models or developing algorithms for business application
- 1+ years of programming in Java, C++, Python or related language experience
- Experience in standard machine-learning and statistical modeling tools and techniques (e.g. random forests, gradient-boosted regression, LASSO, logistic regression)
Preferred qualifications
- Experience in professional software development
- Experience with forecasting and statistical analysis
- Experience in mathematics such as linear programming or nonlinear optimization
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 - Machine Learning, Amazon Transportation 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.
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 applied scientist jobs at this level
Pay
- This job starts at
- $143k
- Typical applied scientist job
- $167k
This posting starts 15% below the typical applied scientist job. See applied scientist jobs
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 algorithms was part of your work. What did you do?
- Tell me about a project where forecasting was part of your work. What did you do?
- Tell me about a project where predictive modeling 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?
Adapt your resume
- List these exact terms on your resume: Machine learning, Algorithms, Forecasting, Predictive Modeling, and Operations Research. 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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