Senior Applied Scientist for Contextual Advertising

5 days ago


London, Greater London, United Kingdom Amazon Full time
Senior Applied Scientist Opportunity

Amazon Advertising is seeking a highly skilled Senior Applied Scientist to lead the development of machine learning and data science initiatives for contextual data processing and classification. As a key member of our team, you will design, prototype, and test hypotheses in a high-ambiguity environment, leveraging analysis and business judgment to drive innovation.

The ideal candidate will have a strong background in machine learning, statistics, and programming, with experience in building large-scale machine learning models and integrating them into complex production systems. You will work closely with software engineering teams to develop and deploy cutting-edge solutions, promoting a culture of experimentation and applied science at Amazon.

Key Responsibilities

  1. Develop and implement machine learning algorithms for contextual data processing and classification.
  2. Collaborate with cross-functional teams to integrate machine learning models into large-scale production systems.
  3. Design and execute experiments to test hypotheses and drive business outcomes.
  4. Communicate complex technical concepts to both technical and non-technical stakeholders.
  5. Stay up-to-date with the latest advancements in machine learning and data science, applying this knowledge to drive innovation and improvement.

About the Team

The Supply Quality organization is responsible for solving optimization problems for ad-programs in Amazon, ensuring high-quality ad-impressions. We develop advanced algorithms and infrastructure systems to optimize performance for our advertisers and publishers. Our team includes experts in distributed computing, machine learning, statistics, optimization, text mining, information theory, and big data systems.

Requirements

PhD in engineering, technology, computer science, machine learning, robotics, operations research, statistics, mathematics, or equivalent quantitative field
- Experience in applied research
- Experience programming in Java, C++, Python, or related language
- Experience building machine learning models for business applications
- Experience with generative deep learning models and specifically LLM and/or LVM development.

Preferred Qualifications

Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy, etc.
- Experience with large-scale distributed systems such as Hadoop, Spark, etc.



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