Applied Scientist , Sponsored Products
Key job responsibilities
Search Supply and Experiences, within Sponsored Products, is seeking an Applied Scientist to join a team with the mandate of creating new ads experience that elevates the shopping experience for our hundreds of millions of customers worldwide. We are looking for a top analytical mind capable of understanding our complex ecosystem of advertisers participating in a pay-per-click model– and leveraging this knowledge to help turn the flywheel of the business.
As an Applied Scientist on this team you will:
- Drive end-to-end machine learning projects that have a high degree of ambiguity, scale and complexity
- Perform analysis on very large data sets to develop ideas and size opportunities; build machine learning models and conduct analysis to demonstrate potential business value
- Design A/B experiments, working with engineers to launch online experiments; conduct statistical analysis of the experimental results to derive understanding
- Build efficient and automated processes for large-scale feature generation, machine-learning model training, validation and serving
- Work with engineers to productionize ML models
- Develop new and innovative machine learning approaches, and collaborate with the science community
About The Team
We are a customer-obsessed team of engineers, technologists, product leaders, and scientists. We are focused on continuous exploration of contexts and creatives where advertising delivers value to customers and advertisers. We specifically work on new ads experiences globally with the goal of helping shoppers make the most informed purchase decision. We obsess about our customers and we are continuously innovating on their behalf to enrich their shopping experience on Amazon.
Basic Qualifications
- 3+ years of building models for business application experience
- PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience
- Experience programming in Java, C++, Python or related language
- Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing
- Experience with neural deep learning methods and machine learning
Preferred Qualifications
- Experience in professional software development
- 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.