Senior Data Scientist, Sponsored Products and Brands

- 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
- 4+ years of data scientist experience
- Bachelor's degree
- Experience with statistical models e.g. multinomial logistic regression
- 2+ years of data visualization using AWS QuickSight, Tableau, R Shiny, etc. experience
- Experience managing data pipelines
- Experience as a leader and mentor on a data science team

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.
Amazon Advertising is one of Amazon's fastest growing and most profitable businesses, responsible for defining and delivering a collection of advertising products that drive discovery and sales. Our products are strategically important to our businesses driving long term growth. We deliver billions of ad impressions and millions of clicks and break fresh ground in product and technical innovations every day!
Amazon is investing heavily in building a world class advertising business and we are responsible for defining and delivering a collection of self-service performance advertising products that drive discovery and sales. Our products are strategically important to our Retail and Marketplace businesses driving long term growth. We deliver billions of ad impressions and millions of clicks daily and are breaking fresh ground to create world-class products. We are highly motivated, collaborative and fun-loving with an entrepreneurial spirit and bias for action. With a broad mandate to experiment and innovate, we are growing at an unprecedented rate with a seemingly endless range of new opportunities.

As a Senior Data Scientist on this team, you will:
- Lead Data Science solutions from beginning to end.
- Deliver with independence on challenging large-scale problems with complexity and ambiguity.
- Write code (Python, R, Scala, SQL, etc.) to obtain, manipulate, and analyze data.
- Build Machine Learning and statistical models to solve specific business problems.
- Retrieve, synthesize, and present critical data in a format that is immediately useful to answering specific questions or improving system performance.
- Analyze historical data to identify trends and support optimal decision making.
- Apply statistical and machine learning knowledge to specific business problems and data.
- Formalize assumptions about how our systems should work, create statistical definitions of outliers, and develop methods to systematically identify outliers. Work out why such examples are outliers and define if any actions needed.
- Given anecdotes about anomalies or generate automatic scripts to define anomalies, deep dive to explain why they happen, and identify fixes.
- Build decision-making models and propose effective solutions for the business problems you define.
- Conduct written and verbal presentations to share insights to audiences of varying levels of technical sophistication.