DESCRIPTION

Are you interested in taking the world’s most broadly adopted and comprehensive cloud platform and architecting and building solutions that will deliver consumer and retail like customer excellence to the recruiting and hiring process at AWS?

About the team
The AWS Talent Acquisition Product Development team is responsible for innovating, architecting, and building, global and scalable technology solutions that transform the recruiting and hiring experience. These solutions will be utilized by thousands of people inside and outside the organization. This team and the solutions we build are a critical component in AWS’s continued growth.

A day in the life
Innovation is at the center of this team. As a Senior Data Scientist you will work collaboratively with a global customer base, program managers, product managers, designers, and engineers to create, refine, and explore ways in which we can transform the recruiting and hiring process at AWS with chat and voice based solutions delivered to users in the flow of work. In this role, you will be a technical expert with significant scope and impact. You will work with Product Managers, Designers, Data Engineers, and Software Engineers to build new ML models to optimize customer experience for the consumption of data and market intelligence. You communicate ideas effectively, drive ideas to detailed product deliverables, and help establish success metrics to optimize results.

BASIC QUALIFICATIONS

· Bachelor's Degree in data science or related disciplines including but not limited to computer engineering/science, management information systems, informatics and analytics.
· 3+ years of experience with data scripting languages (e.g SQL, Python, R etc.) or statistical/mathematical software (e.g. R, SAS, or Matlab)
· Minimum 4 years working as a Data Scientist
Experience with complex data sets and structured and unstructured human perception data, such as data collected on Likert scale via survey platform

PREFERRED QUALIFICATIONS

· Experience in machine-learning methodologies (e.g. supervised and unsupervised learning, deep learning etc.)
· Strong background in statistical methodology, applications to business problems, and/or big data.
· Comfortable communicating with technical and non-technical audiences.
· Able to work in a diverse team of scientists, product managers and program managers
Ability to work on a diverse team or with a diverse range of coworkers