drjobs Sr. Applied Scientist, Inbound Placement Algorithms

Sr. Applied Scientist, Inbound Placement Algorithms

Employer Active

1 Vacancy
drjobs

Job Alert

You will be updated with latest job alerts via email
Valid email field required
Send jobs
Send me jobs like this
drjobs

Job Alert

You will be updated with latest job alerts via email

Valid email field required
Send jobs
Job Location drjobs

Bellevue - USA

Yearly Salary drjobs

$ 150400 - 260000

Vacancy

1 Vacancy

Job Description

The Inventory Planning and Control team is looking for an applied scientist to help build next generation models for supply chain systems in the Supply Chain Optimization Technology (SCOT) group. We own the systems that decide where to place hundreds of millions of units of inventory a week globally shaping Amazons cost structures and value proposition to the customer and ultimately maximizing Amazons long term free cash flow. The work is complex and important to Amazon. There are no textbook solutions to the problems we are solving and very few attempts have been made to solve at Amazons scale which necessitates deep analytical thinking to solve problems.

As a Applied Scientist you will work with other Scientists Software Engineers Product Managers and business teams to understand the current challenges in our inventory systems map these challenges to scientific models innovate solutions using techniques in Operations Research Machine Learning Statistics and Optimization and pick the right tools to deploy these solutions at scale. You will be a part of shaping the future of inventory placement systems at Amazon. Your work will be visible to the business leaders in SCOT and will impact on how we serve our customers so that they get the right product at the right time.


- 3 years of building machine learning models for business application experience
- PhD or Masters degree and 6 years of applied research experience
- Experience programming in Java C Python or related language
- Experience with neural deep learning methods and machine learning

- Experience with modeling tools such as R scikit-learn Spark MLLib MxNet Tensorflow numpy scipy etc.
- Experience with large scale distributed systems such as Hadoop Spark etc.

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 for more information. If the country/region youre applying in isnt listed please contact your Recruiting Partner.

Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $150400/year in our lowest geographic market up to $260000/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge skills and experience. Amazon is a total compensation company. Dependent on the position offered equity sign-on payments and other forms of compensation may be provided as part of a total compensation package in addition to a full range of medical financial and/or other benefits. For more information please visit
This position will remain posted until filled. Applicants should apply via our internal or external career site.


Required Experience:

Senior IC

Employment Type

Full-Time

About Company

Report This Job
Disclaimer: Drjobpro.com is only a platform that connects job seekers and employers. Applicants are advised to conduct their own independent research into the credentials of the prospective employer.We always make certain that our clients do not endorse any request for money payments, thus we advise against sharing any personal or bank-related information with any third party. If you suspect fraud or malpractice, please contact us via contact us page.