Applied Scientist, Modeling and Optimization, Modeling and Optimization (MOP)

Description

Amazon’s Modeling and Optimization (MOP) Team is looking for a passionate individual with strong optimization and analytical skills to join us in the endeavor of designing and improving the most complex transportation and fulfillment network in the world.

The team is responsible for optimizing the global transportation and fulfillment network for Amazon.com and ensuring that the company is able to deliver our customers’ products to them as quickly, accurately, and cost effectively as possible. We design the network that delivers products from vendors and sellers to end customers, through both Amazon’s internal network as well as external partners, using multiple transportation modes. Optimizing the end-to-end network requires deep understanding of inventory management, placement, transportation, and supply chain management. Only through innovative and strategic thing, we will make the right capital investments in technology, buildings and equipment that allows for long-term success.

Key job responsibilities
We are seeking an experienced scientist who has a solid background in Operations Research, Supply Chain Management, Applied Mathematics, or other similar domain.

In this role, you will develop and deploy models and tools that are innovative and scalable to solve new challenges in Amazon's global fulfillment network. You will collaborate with other scientists across teams to create integrated solutions that improves fulfillment speed, cost, and carbon emission. You have deep understanding of business challenges and provide scientific analysis to support business decision using a range of methodologies. You design science tool platforms, deploy models, create data pipelines, or simplify existing processes.

About the team
https://www.linkedin.com/feed/update/urn:li:activity:7089317294417346561/

Basic Qualifications

- 3 years of building machine learning models for business application experience
- PhD, or Master's 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

Preferred Qualifications

- 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 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.