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

Amazon • Bellevue, WA

5d

About The Position

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.

Requirements

• 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

Nice To Haves

• 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.

Responsibilities

• Develop and deploy models and tools that are innovative and scalable to solve new challenges in Amazon's global fulfillment network.
• Collaborate with other scientists across teams to create integrated solutions that improves fulfillment speed, cost, and carbon emission.
• Have deep understanding of business challenges and provide scientific analysis to support business decision using a range of methodologies.
• Design science tool platforms, deploy models, create data pipelines, or simplify existing processes.

Benefits

• 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
• parental leave

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: Ph.D. or professional degree