In this role, you will apply advanced analytics techniques, AI/ML, and statistical concepts to derive insights from massive datasets. The ideal candidate should have expertise in AI/ML, statistical analysis, and the ability to write code for building models and pipelines to automate data and analytics processing. They will help us design experiments, build models, and develop appropriate metrics to deeply understand the strengths and weaknesses of our systems. They will build dashboards to automate data collection and reporting of relevant data streams, providing leadership and stakeholders with transparency into our system's performance. They will turn their findings into actions by writing detailed reports and providing recommendations on where we should focus our efforts to have the largest customer impact.
A successful candidate should be a self-starter, comfortable with ambiguity with strong attention to detail, and have the ability to work in a fast-paced and ever-changing environment. They will also help coach/mentor junior scientists in the team. The ideal candidate should possess excellent verbal and written communication skills, capable of effectively communicating results and insights to both technical and non-technical audiences
BASIC QUALIFICATIONS
- 5+ years of data scientist or similar role involving data extraction, analysis, statistical modeling and communication experience
- 5+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
- Master's degree in a quantitative field such as statistics, mathematics, data science, business analytics, economics, finance, engineering, or computer science, or Bachelor's degree and 8+ years of data scientist or similar role involving data extraction, analysis, statistical modeling and communication experience
- Experience with statistical models e.g. multinomial logistic regression
- Experience with data visualization using Tableau, Quicksight, or similar tools
PREFERRED QUALIFICATIONS
- Experience managing data pipelines
- Experience as a leader and mentor on a data science team
- Experience in forecasting analyses
- Experience with unstructured textual data
- Experience working with scientists, economists, software developers, or product managers
- Experience working with data engineers and business intelligence engineers collaboratively
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.
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.
Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $143,300/year in our lowest geographic market up to $247,600/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.