Key job responsibilities
- Lead science strategy and roadmap to invent and build scalable solutions for Device Advertising personalization and performance.
- Develop and manage a research agenda that balances short term deliverables with measurable business impact as well as long term investments.
- Rapidly design, prototype and test many possible hypotheses in a high-ambiguity environment, making use of both quantitative and business judgment
- Foster cross-team collaboration to execute complex projects, drive alignment across organizations for science, engineering and product strategy to achieve business goals.
- Perform hands-on data analysis, build machine-learning models, run regular A/B tests, and communicate the impact to senior management.
- Collaborate with business and software teams across Amazon Ads, Devices and Prime Video.
- Stay up to date with recent scientific publications relevant to the team
- Build a culture of innovation and long-term thinking, and showcase this via peer-reviewed publications and white papers
- Hire and develop top talent, provide technical and career development guidance to scientists and engineers within and across the organization.
- Effectively communicate complex science problems and solutions to both technical and non-technical audiences.
A day in the life
In this role, you will regularly work with leaders across the advertising organization, including other science teams, product management, and senior leadership. You will also collaborate with science leaders across Amazon Devices and Prime Video organizations to build company-wide alignment. As a leader, you will also manage and work closely alongside your team of applied and data scientists to guide them through high-ambiguity problems and deliver robust, scalable solutions.
About the team
This role is on Device Ads and Personalization (DAPP) team, which is under Amazon Publisher Monetization (APM). This team has a vision to create innovative Ad experiences on Amazon Devices, providing customers better convenience and more selection.
BASIC QUALIFICATIONS
- 4+ years of applied research experience
- 3+ years of scientists or machine learning engineers management experience
- 3+ years of building machine learning models for business application experience
- PhD, or Master's degree and 6+ years of applied research experience
- Knowledge of ML, NLP, Information Retrieval and Analytics
- Experience programming in Java, C++, Python or related language
PREFERRED QUALIFICATIONS
- Experience building complex software systems, especially involving deep learning, machine learning and computer vision, that have been successfully delivered to customers
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 $165,500/year in our lowest geographic market up to $286,000/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.