Applied Scientist II
Amazon
Hyderabad
1d ago
source : Shine

Amazon s location and predictive routing inputs play a crucial role in our vehicle routing problems and other critical applications for Amazon , Prime Now, and other Amazon businesses.

As part of the Last Mile Science & Technology organization, you ll partner closely with ML and Operations Research scientists as well as scientists from other disciplines (e.

g. economics and statistics) in a collegial environment with a clear path to business impact. You will be responsible for developing new predictive and optimization models and algorithms for key applications.

You will be expected to be a thought leader as we chart new courses with our delivery support technologies. Successful candidates will have a deep knowledge of competing statistical and machine learning methods for large scale prediction problems, the ability to map models into production-worthy code, the communication skills necessary to explain complex technical approaches to a variety of stakeholders and customers, and the excitement to take iterative approaches to tackle big, long term problems.

Basic Qualification :

PhD in Computer Science, Mathematics, Statistics, or other quantitative field with exposure to statistical modeling and machine learning

3+ years of applying machine learning for solving real-world problems in industry

Proficiency in C / C++, Java, or Python

Proficiency with at least one machine learning or statistical modeling library (R, Matlab, Scikit-learn)

Past delivery of large-scale ML solutions for complex business problems

Outstanding written and verbal communication skills

Preferred Qualifications :

Publications in top ML conferences or journals

Experience with a popular deep learning toolkit (TensorFlow, MXNet, PyTorch, Caffe etc), PhD in Computer Science, Mathematics, Statistics, or other quantitative field with exposure to statistical modeling and machine learning

3+ years of applying machine learning for solving real-world problems in industry

Proficiency in C / C++, Java, or Python

Proficiency with at least one machine learning or statistical modeling library (R, Matlab, Scikit-learn)

Past delivery of large-scale ML solutions for complex business problems

Outstanding written and verbal communication skills

Publications in top ML conferences or journals

Experience with a popular deep learning toolkit (TensorFlow, MXNet, PyTorch, Caffe etc)

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