Machine Learning Scientist

Job description

DESCRIPTION

How do we identify products that our customers are interested in? How do we make buying decisions on millions of new and slow-moving products with no demand signals? How do we continuously explore our product offering and quantify the value of our investment decisions? The Fringe Selection team in the Supply Chain Optimization Technologies (SCOT) organization is dedicated to answering these questions using statistical methods. We are responsible for driving thought leadership and innovation to define new approaches for optimizing Amazon's selection. We develop cutting edge data pipelines, build accurate predictive models, and deploy automated software solutions to bring the right selection to our customers.

As a Machine Learning Scientist at Amazon, you will connect with leaders in your field working on similar problems. You will work closely with software engineers, product managers and other Amazon research scientists to lead the end-to-end process of identifying the problem, designing, building and deploying predictive, scalable machine learning models and scientifically measuring their impact on our selection and profitability. The ideal candidate will be an expert in the areas of data science, machine learning and statistics. You will be able to balance technical leadership with strong business judgment to make the right decisions about technology, models and methodologies choices. You will strive for simplicity, and demonstrate significant creativity and high judgment backed by statistical proof.

Desired profile

BASIC QUALIFICATIONS

· MS in Data Science, Machine Learning, Statistics, Computer Science, Applied Math or equivalent highly technical field.
· Practical experience in applying fundamental machine learning algorithms to solve complex problems
· Experience with modifying standard algorithms (e.g. changing objectives, working-out the math, implementing and scaling)
· 5+ years experience in one or more major programming languages (Python, Java, C++, C, Perl/Ruby, etc...
· 5+ years experience building machine learning models deployed to production environments.
· Proven ability to implement and operate at large scale.
· Have a history of building systems that capture and utilize large data sets in order to quantify your products performance via metrics or KPIs.
· Experienced in computer science fundamentals such as object-oriented design, data structures and algorithm design