Amazon is investing heavily in building a world class advertising business and we are responsible for defining and delivering a collection of advertising products that drive discovery and sales. Our products are strategically important to our Retail and Marketplace businesses driving long term growth. We deliver billions of ad impressions and millions of clicks daily and are breaking fresh ground to create world-class products. We are highly motivated, collaborative and fun-loving with an entrepreneurial spirit and bias for action. With a broad mandate to experiment and innovate, we are growing at an unprecedented rate with a seemingly endless range of new opportunities.
We are looking for top Applied Scientists who have a deep passion for building machine-learning solutions, ability to communicate data insights and scientific vision, and execute strategic projects.
As an Applied Scientist in Machine Learning, you will: · Build machine learning models and utilize data analysis to deliver scalable solutions to business problems. · Run A/B experiments, gather data, and perform statistical analysis. · Establish scalable, efficient, automated processes for large-scale data analysis, machine-learning model development, model validation and serving. · Work closely with software engineers on detailed requirements, technical designs and implementation of end-to-end solutions in production · Research new machine learning approaches.
· M.S. or Ph.D. in Computer Science, Information Retrieval, Machine Learning, Statistics, Applied Mathematics, Natural Language Processing, or related discipline. · Breadth and depth knowledge of machine learning algorithms and best practices. · At least 2 years of hands-on experience in building Machine Learning solutions to solve real-world problems. · At least 2 years of experience with computer science fundamentals in object-oriented design, data structures, algorithm design, problem solving, and complexity analysis. · At least 2 years of experience with, at least, one model programming language such as Java, Python, Scala, C++. · Ph.D. in quantitative field with a strong Machine Learning background. · 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, Lucene/SOLR or Storm/Samza.