Workforce Staffing (WFS) brings together the workforce powering Amazon’s ability to delight customers: the Amazon Associate. With over 1M hires, WFS supports sourcing, hiring, and developing the best talent to work in our fulfillment centers, sortation centers, delivery stations, shopping sites, Prime Air locations, and more.
WFS' Funnel Science and Analytics team is looking for a Research Scientist. This individual will be responsible for conducting experiments and evaluating the impact of interventions when conducting experiments is not feasible. The perfect candidate will have the applied experience and the theoretical knowledge of policy evaluation and conducting field studies.
Key job responsibilities
- As a Research Scientist (RS), you will do causal inference, design studies and experiments, leverage data science workflows, build predictive models, conduct simulations, create visualizations, and influence science and analytics practice across the organization.
- Provide insights by analyzing historical data from databases (Redshift, SQL Server, Oracle DW, and Salesforce).
- Identify useful research avenues for increasing candidate conversion, test, and create well written documents to communicate to technical and non-technical audiences.
About the team
Funnel Science and Analytics team finds ways to maximize the conversion and early retention of every candidate who wants to be an Amazon Associate. By focusing on our candidates, we improve candidate and business outcomes, and Amazon takes a step closer to being Earth’s Best Employer.
- 2+ years experience in causal modeling (e.g., graphical models, causal Bayesian network, potential outcomes, A/B testing, experiments, quasi-experiments) and science workflows (e.g., regularized regression, random forest, LightGBM); obtained from previous work experience or through a Master’s degree or higher (e.g., Epidemiology, Business Analytics, Public Policy, Sociology, Economics, Marketing, Science, Statistics, Mathematics, Engineering, Computer Science, or related analytical disciplines).
- Proficient in one scripting language (e.g., R, Python).
- Experience with survey methodology, discrete choice modeling, and cost-benefit analysis.
- Experience with applying systems dynamics principles, computational modeling, and system simulation.
- Experience with AWS Machine Learning workflows (e.g., SageMaker).
- Experience with hosting production quality code in AWS infrastructure.
- Experience with applying science in HR, Marketing, Advertising, or the social and behavioral sciences.
- Experience creating prototypes and interactive visualization.
- Experience with optimization techniques and algorithms and computational social science.
- Experience consulting with senior management and executives in a fast-paced environment.
Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us.