Key job responsibilities
• Define and execute a research and development plan that enables data-driven marketing decisions and delivers inspiring customer experiences
• Evaluate, evolve, and invent scientific techniques to effectively address customer needs and business problems
• Establish and drive science prototyping best practices to ensure coherence and integrity of data feeding into production ML/AI solutions
• Collaborate with colleagues across science and engineering disciplines for rapid prototyping at scale
• Partner with engineering teams to solve complex technical problems, define system-level requirements, develop implementation plans, and guide the adaptation of techniques to meet production needs
• Partner with product managers and stakeholders to define forward-looking product visions and prospective business use-cases
• Drive and lead of culture of data-driven innovation within and outside across Amazon Ads Marketing organization
• Influence organizational vision across Ads Marketing organization
About the team
The Marketing Decisions Science team provides AI/ML products to enable Amazon Ads Marketing to deliver relevant and compelling guidance, education, and inspiration to prospective and active advertisers across marketing channels. We own the product, technology, and deployment roadmap for AI/ML products across Amazon Ads Marketing. We analyze the needs, experiences, and behaviors of Amazon advertisers at petabytes scale, to deliver the right marketing communications to the right advertiser at the right time. Our products enable applications and synergies across Ads organization, spanning marketing, product, and sales use cases.
BASIC QUALIFICATIONS
- 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
PREFERRED QUALIFICATIONS
- 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. 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 $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.