Senior Applied Scientist, Shopping Convo Foundations - Pre-purchases Science
Core
Lead research and development of novel machine learning approaches to solve complex catalogue expansion and product attribute challenges, translating scientific breakthroughs into production-ready solutions.
Role type
Senior Applied Scientist (Catalogue Expansion & Product Attributes)
Builds
Production ML models for product catalogue coverage and attribute extraction
Domain
E-commerce, Catalogue Management, Machine Learning
Deliverable
production ML models
Required skills
Machine learning model development, Neural deep learning methods, Java, C++, Python, Experimentation design, Model optimization, Scalability engineering, Low-latency solution deployment, Team leadership
Preferred skills
Large scale distributed systems, Modeling tools (R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy)
Technologies
Java, C++, Python, Spark, Hadoop, Tensorflow, MxNet, scikit-learn, numpy, scipy
Responsibilities
Design and develop state-of-the-art ML models, Conduct rigorous experimentation, Translate scientific breakthroughs into production-ready solutions, Guide junior scientists, Optimize model performance and ensure scalability, Deploy low-latency solutions at Amazon scale
Seniority
Senior, hands-on IC with mentorship