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# Senior Applied Scientist, Modeling and Optimization

- **Company:** Amazon.com, Inc.
- **Location:** Santa Clara, CA, United States
- **Experience:** Expert
- **Salary:** $192,200.0 - $260,000.0
- **Contract:** Permanent contract
- **Skills:** Mxnet, Java (Programming Language), Business Software, C++ (Programming Language), Data Structures, Perl (Programming Language), R (Programming Language), Network Topologies, Python (Programming Language), Machine Learning, Routing, NumPy, Software Tools, Tensorflow, SciPy, Software Engineering, Spark Mllib, Scikit Learn, Information Technology, Programming Languages
- **Published:** July 12, 2026
- **Apply:** https://dejobs.org/x/x/54701221D9E5438EA57BE93FD65BE8BB/job/

## About the Role

* 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

Preferred Qualifications

 * Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.
 * Experience in applied research

## Description

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.


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