Sr. Applied Scientist, Amazon Transportation

Amazon • Santa Clara, CA

1d

About The Position

Amazon’s Middle Mile Planning Research and Optimization Science group (mmPROS)
is looking for a Senior Applied Scientist specializing in design and evaluation
of algorithms for predictive modeling and optimization applied to large-scale
transportation planning systems. This includes the development of novel machine
learning and artificial intelligence techniques to improve on marketplace
optimization solutions.

The Middle Mile Science group is charged with developing an evolving suite of
optimization tools to facilitate the design of efficient air and ground
transport networks, optimize the flow of packages within the network to
efficiently align network capacity and shipment demand, set prices, and
effectively utilize scarce resources, such as aircraft and trucks. The scale of
Amazon’s fulfillment operations challenges us to design, build and operate
robust transportation networks that minimize the overall operational cost while
meeting all customer deadlines. Real-time execution of our network depends on
state-of-the-art artificial intelligence tools to coordinate the actions of
thousands of operators and drivers in real time. Amazon often finds existing
techniques do not effectively match our unique business needs, which
necessitates the innovation and development of new approaches and algorithms to
find an adequate solution.

As a Sr. Applied Scientist responsible for middle mile transportation, you will
be working closely with different teams including business leaders and engineers
to design and build scalable products operating across multiple transportation
modes. You will create experiments and prototype implementations of new learning
algorithms and prediction techniques. You will have exposure to top level
leadership to present findings of your research. You will also work closely with
other scientists and engineers to implement your models within our production
system. You will implement solutions that are exemplary in terms of algorithm
design, clarity, model structure, efficiency, and extensibility, and make
decisions that affect the way we build and integrate algorithms across our
product portfolio.

About the team
Our Middle Mile Marketplace Science team builds the algorithms for Amazon’s
rapidly growing freight marketplace. Amazon contracts with 3P shippers and a
network of independent carriers, using a mix of contract structures with varying
service and risk profiles. Our work focuses on mechanisms and learning
algorithms to optimize pricing and matching in this complex marketplace, and
continually improve the experience for carriers and shippers. This is an area
with many challenging problems and a huge business impact for Amazon!

Requirements

• 5+ years of building machine learning models or developing algorithms for business application experience
• PhD in engineering, technology, computer science, machine learning, robotics, operations research, statistics, mathematics or equivalent quantitative field, or Master's degree and 10+ years of industry or academic research experience
• Computer Science fundamentals in algorithm design, problem solving, and complexity analysis
• Proficiency in, at least, one modern programming language such as C, C++, Java, Python
• Excellent communication skills with both technical and non-technical audiences

Nice To Haves

• Significant peer-reviewed scientific contributions in premier journals and conferences
• Hands-on experience with neural deep learning, reinforcement learning, and machine learning technologies
• Experience working with AWS technologies

Responsibilities

• design and build scalable products operating across multiple transportation modes
• create experiments and prototype implementations of new learning algorithms and prediction techniques
• present findings of your research to top level leadership
• work closely with other scientists and engineers to implement your models within our production system
• implement solutions that are exemplary in terms of algorithm design, clarity, model structure, efficiency, and extensibility
• make decisions that affect the way we build and integrate algorithms across our product portfolio

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