Applied Scientist, Contextual Ads

Amazon Advertising is looking for an Applied Scientist to join its initiative that powers Amazon’s contextual advertising products.

Advertising at Amazon is a fast-growing multi-billion dollar business that spans across desktop, mobile and connected devices; encompasses ads on Amazon and a vast network of hundreds of thousands of third party publishers; and extends across US, EU and an increasing number of international geographies.The Supply Quality organization has the charter to solve optimization problems for ad-programs in Amazon and ensure high-quality ad-impressions. We develop advanced algorithms and infrastructure systems to optimize performance for our advertisers and publishers. We are focused on solving a wide variety of problems in computational advertising like Contextual data processing and classification, traffic quality prediction (robot and fraud detection), Security forensics and research, Viewability prediction, Brand Safety and experimentation. Our team includes experts in the areas of distributed computing, machine learning, statistics, optimization, text mining, information theory and big data systems.

We are looking for a dynamic, innovative and accomplished Applied Scientist to work on machine learning and data science initiatives for contextual data processing and classification that power our contextual advertising solutions. Are you excited by the prospect of analyzing terabytes of data and leveraging state-of-the-art data science and machine learning techniques to solve real world problems? Do you like to own business problems/metrics of high ambiguity where yo get to define the path forward for success of a new initiative? As an applied scientist, you will invent ML based solutions to power our contextual classification technology. As this is a new initiative, you will get an opportunity to act as a thought leader, work backwards from the customer needs, dive deep into data to understand the issues, conceptualize and build algorithms and collaborate with multiple cross-functional teams.


Key job responsibilities
* Design, prototype and test many possible hypotheses in a high-ambiguity environment, making use of both analysis and business judgment.
* Collaborate with software engineering teams to integrate successful experiments into large-scale, highly complex Amazon production systems.
* Promote the culture of experimentation and applied science at Amazon.
* Demonstrated ability to meet deadlines while managing multiple projects.
* Excellent communication and presentation skills working with multiple peer groups and different levels of management
* Influence and continuously improve a sustainable team culture that exemplifies Amazon’s leadership principles.

BASIC QUALIFICATIONS

- PhD, or a Master's degree and experience in CS, CE, ML or related field
- Experience in patents or publications at top-tier peer-reviewed conferences or journals
- Experience programming in Java, C++, Python or related language
- Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing
- Experience in building machine learning models for business application

PREFERRED QUALIFICATIONS

- Experience using Unix/Linux
- Experience in professional software development
- Experience with Artificial General Intelligence, generative deep learning models, and specifically LLM development.