Senior Manager, Applied Science, Prime Video Advertising

Amazon Amazon · Big Tech · NY +1 · Applied Science

Senior Manager, Applied Science at Amazon Prime Video Advertising, leading a team to build and scale ML/AI solutions for advertising optimization, experimentation, and generative AI-powered ad creative generation. The role involves setting scientific vision, managing managers, and driving strategic initiatives in a rapidly growing business.

What you'd actually do

  1. Ad Load Optimization – Balancing advertising revenue with viewer engagement through sophisticated ML models that determine optimal ad frequency, placement, and duration
  2. Yield Optimization – Maximizing advertising revenue through intelligent allocation, pricing, and forecasting models
  3. Experimentation & Metrics – Designing and scaling experimentation frameworks and causal inference methods to measure the impact of advertising decisions on both business outcomes and customer experience
  4. Ad Creative Generation & Augmentation – Leveraging generative AI to create, personalize, and enhance ad creatives at scale

Skills

Required

  • Machine Learning
  • Deep Learning
  • ML Engineering
  • Optimization
  • Causal Inference
  • NLP/Generative AI
  • Recommendation Systems
  • Leadership
  • Team Management
  • Scientific Vision
  • Strategic Research Project Management

Nice to have

  • Advertising Technology
  • Ad Marketplaces
  • Revenue Optimization
  • Real-time Bidding
  • Auction Optimization
  • Content Personalization
  • Large Language Models
  • Hybrid Science/Engineering Team Management
  • Experimentation Platforms
  • External Scientific Community Engagement
  • Communication to Senior Leadership

What the JD emphasized

  • lead a team of scientists and engineers
  • own the science strategy and execution
  • set the 3-5 year scientific vision
  • build and develop a high-performing team of senior scientists and managers
  • drive large-scale ML/AI initiatives
  • working at the intersection of machine learning, generative AI, causal inference, and advertising technology
  • PhD in Computer Science, Computer Engineering, Machine Learning, Statistics, Operations Research, or a related quantitative field
  • Experience as a science manager, with demonstrated experience managing other managers or leading science teams through senior leaders
  • Extensive track record of solving complex business problems with machine learning, deep learning, and ML engineering at scale
  • Proven ability to hire, develop, and manage a high-performing applied science organization, including growing future science leaders
  • Experience delivering a scientific vision with a path to execution, including managing strategic research projects spanning multiple years
  • Strong technical depth in machine learning with the ability to evaluate and guide work across optimization, causal inference, NLP/generative AI, and recommendation systems
  • Experience driving large-scale scientific efforts and making trade-offs between opportunity, resources, and business impact

Other signals

  • leading a team of scientists and engineers building ML/AI solutions
  • shaping the science strategy and execution for key workstreams
  • driving large-scale ML/AI initiatives
  • working at the intersection of machine learning, generative AI, causal inference, and advertising technology