Amazon Sr Applied Scientist Sponsored products ads response prediction 

United States, New York, New York 

532707689

As an, you will:- Conduct hands-on data analysis, build large-scale machine-learning models and pipelines
- Work closely with software engineers on detailed requirements, technical designs and implementation of end-to-end solutions in production- Establish scalable, efficient, automated processes for large-scale data analysis, machine-learning model development, model validation and serving
- Provide technical leadership, research new machine learning approaches to drive continued scientific innovation- Help attract and recruit technical talent
- Ph.D. in Computer Science, Information Retrieval, Machine Learning, Natural Language Processing, Statistics, Applied Mathematics, or related discipline
- Breadth and depth knowledge of machine learning algorithms and best practices
- At least 5 years of hands-on experience in building Machine Learning solutions to solve real-world problems
- At least 3 years of experience with computer science fundamentals in object-oriented design, data structures, algorithm design, problem solving, and complexity analysis
- At least 3 years of experience with, at least, one modern programming language such as Java, Python, Scala, C++
- Experience in building large-scale machine-learning models for online recommendation, ads ranking, personalization, or search, etc.
- Experience with Big Data technologies such as AWS, Hadoop, Spark, Pig, Hive
- Strong proficiency with Java, Python, Scala or C++
- Experience in computational advertising technology is a big plus
- Published research work in academic conferences or industry circles
- Excellent oral and written communication skills, with the ability to communicate complex technical concepts and solutions to all levels of the organization

- 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

- 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.