Job Description

DESCRIPTION

Amazon is looking for a truly innovative and technically strong research scientist with a background in econometric analysis, statistical inference, and machine learning.

As a Research Scientist, you will:
Apply your quantitative modeling skills to complex decision-making problems using noisy data coming from various data sources such as medical claims, electronic medical records, patient reported outcomes, customer satisfaction surveys, and system-generated timestamped data.
Work closely with stakeholders and translate data-driven findings into actionable insights.
About You:
Problem Solver: Ability to utilize exceptional problem-solving skills to work through different challenges in ambiguous situations.
Doer: Youve successfully delivered end-to-end analytical projects, working through conflicting viewpoints and data limitations.
Detail Oriented: You have an enviable level of attention to details, and catch things that others miss.
Communicator: Ability to communicate analytical results to senior leaders, and peers.
Influencer: Innovative scientist with the ability to identify opportunities in a fast-paced and ever-changing environment, and gain support with data and storytelling.
Here at Amazon, we embrace our differences. We are committed to furthering our culture of inclusion. We have innovative benefit offerings, and we host annual and ongoing learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences. Amazons culture of inclusion is reinforced within our 14 Leadership Principles, which remind team members to seek diverse perspectives, learn and be curious, and earn trust.

Our team also puts a high value on work-life balance. Striking a healthy balance between your personal and professional life is crucial to your happiness and success here, which is why we arent focused on how many hours you spend at work or online. Instead, were happy to offer a flexible schedule so you can have a more productive and well- balanced lifeboth in and outside of work.

Our team is dedicated to supporting new members. We have a broad mix of experience levels and tenures, and were building an environment that celebrates knowledge sharing and mentorship. Our senior members enjoy one-on-one mentoring and thorough, but kind, code reviews. We care about your career growth and strive to assign projects based on what will help each team member develop into a better-rounded engineer and enable them to take on more complex tasks in the future.
BASIC QUALIFICATIONS

MS. in Health Economics, Statistics, Operations Research, Machine Learning, Computer Science, or a related quantitative field.
2+ years of experience with data scripting languages (e.g., SQL, Python, R, etc.).
2+ years research experience.
2+ years of hands-on experience with various statistical modeling, machine learning, and data analysis tools and techniques, and parameters that affect their performance.
2+ years of experience in programming in R, Python, Scala or similar languages.
2+ years of experience with data visualization and presentation, turning complex analysis into insights.

PREFERRED QUALIFICATIONS

Ph.D. in Health Economics, Statistics, Operations Research, Machine Learning, Computer Science, or a related quantitative field.
Familiarity with standard methods for measuring health care utilization, spending, quality, and outcomes; risk adjustment; provider profiling; and related analytical tasks.
Excellent quantitative modeling, data analysis, and problem-solving skills. Sophisticated user of econometrics and statistical tools.
Experience collaborating with software development teams, data scientists, business intelligence or other technical roles.
Proven ability to work effectively in a cross-functional team and demonstrable track record dealing well with ambiguity, prioritizing needs, and delivering results in an agile, dynamic environment.
Superior verbal and written communication and presentation skills, ability to convey rigorous mathematical concepts and considerations to non-experts.
Demonstrable track record dealing well with ambiguity, prioritizing needs, and delivering results in an agile, dynamic environment.
Strong object-oriented design and coding skills (Java, C/C++, or Python).
Publication record in peer-reviewed journals and conferences.
Familiarity with optimization modeling and tools (e.g., Cplex, Gurobi, Xpress, etc.).

Amazon is committed to a diverse and inclusive workforce. Amazon is an equal opportunity employer and does not discriminate on the basis of race, ethnicity, 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.