Applied Scientist, Sales AI

Amazon Amazon · Big Tech · Seattle, WA · Applied Science

This role focuses on applying AI/ML, particularly Generative AI, to optimize the Ad Sales business by creating actionable insights and recommendations for account teams and improving their end-to-end workflows. The scientist will build and refine models using statistical methods, deep learning, and reinforcement learning, and leverage NLP and Generative AI for explainability. The role involves research, A/B testing, collaboration with engineering and product teams, and translating complex findings into business recommendations.

What you'd actually do

  1. Conceptualize and lead state-of-the-art research on new Machine Learning and Generative Artificial Intelligence solutions to optimize all aspects of the Ad Sales business
  2. Lead the technical approach for the design and implementation of successful models and algorithms in support of expert cross-functional teams delivering on demanding projects
  3. Run regular A/B experiments, gather data, and perform statistical analysis
  4. Partner with software engineering and product management teams to support product and service development, define success metrics and measurement approaches, and help drive adoption of innovative new features for our services.
  5. Translate complex scientific findings into actionable business recommendations for stakeholders and senior management

Skills

Required

  • 3+ years of building models for business application experience
  • PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience
  • 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

Nice to have

  • Experience using Unix/Linux
  • Experience in professional software development

What the JD emphasized

  • state-of-the-art research
  • Machine Learning and Generative Artificial Intelligence solutions
  • optimize all aspects of the Ad Sales business
  • models and algorithms
  • expert cross-functional teams
  • demanding projects
  • A/B experiments
  • statistical analysis
  • scalability
  • efficiency
  • automation
  • large-scale data analytics
  • model training
  • deployment
  • serving
  • software engineering
  • product management
  • product and service development
  • success metrics
  • measurement approaches
  • adoption
  • innovative new features
  • requirements gathering
  • business stakeholders
  • scientific documentation
  • product initiatives
  • end-to-end solutions
  • production
  • actionable business recommendations
  • stakeholders
  • senior management
  • clear, compelling reports
  • presentations
  • showcase results
  • identify best practices
  • Sales AI
  • selling motions
  • account team workflows
  • state-of-the-art of AI/ML services
  • sales intelligence models
  • advertiser insights
  • recommendations
  • Generative AI-powered applications
  • account team workflows
  • patents or publications at top-tier peer-reviewed conferences or journals

Other signals

  • Generative AI
  • account teams
  • actionable insights
  • recommendations
  • end-to-end workflows
  • work efficiency
  • modeling dynamic systems
  • statistical methods
  • deep learning
  • reinforcement learning
  • operations research
  • natural language processing
  • generative AI
  • explainability
  • ad sales support technologies
  • complex technical approaches
  • stakeholders
  • customers
  • iterative approaches
  • long-term problems
  • latest generative AI systems and services
  • high quality
  • Machine Learning
  • Generative Artificial Intelligence solutions
  • optimize
  • Ad Sales business
  • models and algorithms
  • expert cross-functional teams
  • demanding projects
  • A/B experiments
  • statistical analysis
  • scalability
  • efficiency
  • automation
  • large-scale data analytics
  • model training
  • deployment
  • serving
  • software engineering
  • product management
  • product and service development
  • success metrics
  • measurement approaches
  • adoption
  • innovative new features
  • requirements gathering
  • business stakeholders
  • scientific documentation
  • product initiatives
  • end-to-end solutions
  • production
  • actionable business recommendations
  • senior management
  • clear, compelling reports
  • presentations
  • showcase results
  • identify best practices
  • Sales AI
  • selling motions
  • account team workflows
  • state-of-the-art of AI/ML services
  • sales intelligence models
  • advertiser insights
  • recommendations
  • Generative AI-powered applications
  • account team workflows