Description

We are looking for a research scientist with expertise in applying causal inference, experimental design, or causal machine learning techniques to topics in labor, personnel, education, health, public, or behavioral science. We are particularly interested in candidates with experience applying these skills to strategic problems with significant business and/or social policy impact.

Candidates will work with economists, scientists, and engineers to estimate and validate their models on large scale data, and will help business partners turn the results of their analysis into policies, programs, and actions that have a major impact on Amazon’s business and its workforce. We are looking for creative thinkers who can combine a strong scientific toolbox with a desire to learn from others, and who know how to execute and deliver on big ideas.

You will conduct, direct, and coordinate all phases of research projects, including defining key research questions, developing models, designing and implementing appropriate data collection methods, executing analysis plans, and communicating results. You will earn trust from our business partners by collaborating with them to define key research questions, communicate scientific approaches and findings, listen to and incorporate their feedback, and deliver successful solutions

About the team

The People eXperience and Technology Central Science Team (PXTCS) uses economics, behavioral science, statistics, and machine learning to proactively identify mechanisms and process improvements which simultaneously improve Amazon and the lives, wellbeing, and the value of work to Amazonians. We are an interdisciplinary team that combines the talents of science and engineering to develop and deliver solutions that measurably achieve this goal.

Basic Qualifications

• PhD or equivalent Master's degree plus 10+ years of research experience in a quantitative field.

• Experience investigating the feasibility of applying scientific principals and concepts to business problems and products.

• 2+ years of research or work experience in the following skill(s): programming with a mathematical programming language such as R, MATLAB, or SAS or major programming language such as Python, Java, C++, C#, or C.

Preferred Qualifications

• Ph.D. in in a quantitative social science (e.g. economics, quantitative psychology, quantitative sociology, etc.).

• 5+ years of experience conducting large-scale applied research studies, including experience on topics relating to labor, personnel, education, health, public, or behavioral science.

• Experience applying machine learning and predictive models to forecasting, data mining, feature selection for regression, and/or causal models.

• Experience conducting statistical inference, hypothesis testing, and fitting ML predictive models using large administrative and survey databases.

• Superior verbal and written communication and presentation skills, ability to convey rigorous mathematical concepts and considerations to non-experts.

• Experience leading research projects with multiple stakeholders.

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.

Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $170,500/year in our lowest geographic market up to $294,700/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits. This position will remain posted until filled. Applicants should apply via our internal or external career site.