Applied Scientist - Denied Party Screening

Job description

DESCRIPTION

In the Consumer Cloud Security group we build automatic mechanisms to detect and prevent prohibited transactions with denied parties. We are looking for an Applied Scientist to lead the technical vision and architecture for a new mission critical system that screens customers from the moment they are introduced to Amazon and at every point they interact and transact with Amazon's various businesses and products. This is a greenfield initiative with plenty of opportunity to innovate and deliver.

You will collaborate with the leadership team to drive key engineering and business decisions that will influence the Amazon transaction compliance. You will use Amazon's large-scale computing resources to build models and you will work with domain experts and engineers to help turn those models into production solutions. You will participate in the Amazon ML community and mentor software development engineers with a strong interest in and knowledge of ML.

We are looking for passionate, hard-working, and talented Applied scientist who have experience building mission critical, high volume applications. You will have an enormous opportunity to make a large impact on the design, architecture, and implementation of cutting edge products used every day by all Amazon businesses.

Desired profile

BASIC QUALIFICATIONS

· M.S. or PhD in Computer Science, Machine Learning, Operational Research, Statistics, or a other quantitative field;
· 3+ years of practical experience applying ML to solve complex problems;
· Algorithm and model development experience for large-scale applications;
· Experience using Java, C++, or other programming language, as well as with R or Python;
· Experience distilling informal customer requirements into problem definitions, dealing with ambiguity and competing objectives.