Data Scientist II, Workforce Intelligence

DESCRIPTION

Do you want a role with deep meaning and the ability to make a major impact? As part of Intelligent Talent Acquisition (ITA), you'll have the opportunity to reinvent the hiring process and deliver unprecedented scale, sophistication, and accuracy for Amazon Talent Acquisition operations. ITA is an industry-leading people science and technology organization made up of scientists, engineers, analysts, product professionals and more, all with the shared goal of connecting the right people to the right jobs in a way that is fair and precise. Last year we delivered over 6 million online candidate assessments, and helped Amazon deliver billions of packages around the world by making it possible to hire hundreds of thousands of workers in the right quantity, at the right location and at exactly the right time. You’ll work on state-of-the-art research, advanced software tools, new AI systems, and machine learning algorithms, leveraging Amazon's in-house tech stack to bring innovative solutions to life. Join ITA in using technologies to transform the hiring landscape and make a meaningful difference in people's lives. Together, we can solve the world's toughest hiring problems.

Key job responsibilities
o Lead quantitative analyses and develop statistical models using Python, R, and other programming languages to:
 Solve complex business challenges through data-driven insights
 Identify patterns and trends in large datasets
 Create predictive models to optimize business outcomes
 Implement and validate statistical methodologies
o Develop comprehensive technical documentation including:
 Detailed methodology reports
 Model specifications and assumptions
 Statistical analysis procedures
 Validation results and model performance metrics
 Implementation guidelines and recommendations

BASIC QUALIFICATIONS

- 3+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
- 2+ years of data scientist experience
- 3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience
- Bachelor's degree
- Experience applying theoretical models in an applied environment