Senior Applied Scientist, Modeling and Optimization

Amazon • Santa Clara, CA

4d

About The Position

Amazon is looking for a motivated individual with strong analytical and
algorithmic skills and practical experience to join the Modeling and
Optimization (MOP) Routing Science team. Your main focus will be on developing
and improving our last-mile experience, with emphasis on algorithmic and
analytical work. We are looking for candidates with proven ability to design,
implement, and evaluate state-of-the-art solutions to large-scale optimization
problems, working closely with software development engineers. The position
requires strong background in combinatorial optimization, algorithms, algorithm
engineering, and data structures, particularly as it applies to vehicle routing
and related problems. Familiarity with Data Science and Machine Learning
techniques is a plus.

You will also play an integral role in the network planning, modeling, and
analysis that will improve the efficiency and cost effectiveness of global
fulfillment operations. You will identify and evaluate opportunities to reduce
variable costs by improving the transportation network topology, inventory
placement, transportation operations and scheduling, fulfillment center
processes, and the execution to operational plans. You will also improve the
efficiency of capital investment by helping plan the location and deployment of
fixed assets. Finally, you will help create the metrics to quantify improvements
to the fulfillment costs (e.g., transportation and labor costs) resulting from
the application of these optimization models and tools.

Requirements

• 3+ 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
• Knowledge of programming languages such as C/C++, Python, Java or Perl
• Strong background in combinatorial optimization, algorithms, algorithm engineering, and data structures, particularly as it applies to vehicle routing and related problems.

Nice To Haves

• Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.
• Experience in applied research
• Familiarity with Data Science and Machine Learning techniques

Responsibilities

• Developing and improving our last-mile experience, with emphasis on algorithmic and analytical work.
• Design, implement, and evaluate state-of-the-art solutions to large-scale optimization problems, working closely with software development engineers.
• Play an integral role in the network planning, modeling, and analysis that will improve the efficiency and cost effectiveness of global fulfillment operations.
• Identify and evaluate opportunities to reduce variable costs by improving the transportation network topology, inventory placement, transportation operations and scheduling, fulfillment center processes, and the execution to operational plans.
• Improve the efficiency of capital investment by helping plan the location and deployment of fixed assets.
• Help create the metrics to quantify improvements to the fulfillment costs (e.g., transportation and labor costs) resulting from the application of these optimization models and tools.

Benefits

• 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.
• full range of medical, financial, and/or other benefits

What This Job Offers

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