Staff Data Scientist, Discover Personalization and Quality

Google Google · Big Tech · Mountain View, CA +2

Staff Data Scientist role focused on personalization and quality for Google Discover, involving the development and improvement of retrieval and ranking ML systems. The role requires leveraging AI and LLM techniques to enhance user experience and product growth, with responsibilities including analysis, research, and technical leadership.

What you'd actually do

  1. Lead core understanding of retrieval and ranking ML systems and collaborate with engineers to deliver significant improvements that accelerate product growth.
  2. Analyze systems to identify opportunities while maintaining end-to-end ownership of research agenda, execution, and insight delivery to leadership.
  3. Build expertise in retrieval and ranking systems, advocating for changes, where needed, and driving cross-functional alignment.
  4. Contribute as an individual contributor, as well as a Technical Lead for a small group of data scientists.
  5. Manage ambiguous data science problems, and leveraging new technology to produce quantum leaps forward in understanding, such as via LLM-driven tooling.

Skills

Required

  • Master's degree in Statistics, Data Science, Mathematics, Physics, Economics, Operations Research, Engineering, or a related quantitative field.
  • 8 years of work experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or 6 years of work experience with a PhD degree.

Nice to have

  • Familiarity with modern Machine Learning and Large Language Model (LLM) techniques.
  • Ability to commit to knowledge and learning, respect for science, tolerance for ambiguity, and interest in practical application of science to business.
  • Excellent collaboration skills, with the ability to collaborate cross-functionally and work effectively with Data Scientist (DS), User Experience Researcher (UXR), product and engineering partners.
  • 10 years of work experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or 8 years of work experience with a PhD degree.

What the JD emphasized

  • retrieval and ranking ML systems
  • retrieval and ranking systems
  • LLM-driven tooling

Other signals

  • Leverage a wide range of analysis tools (including metrics and AI raters, statistical modeling, cohort and exploratory analyses), and incorporate AI-driven understanding to define the job of a data scientist for the new era.
  • Lead core understanding of retrieval and ranking ML systems and collaborate with engineers to deliver significant improvements that accelerate product growth.
  • Analyze systems to identify opportunities while maintaining end-to-end ownership of research agenda, execution, and insight delivery to leadership.
  • Build expertise in retrieval and ranking systems, advocating for changes, where needed, and driving cross-functional alignment.
  • Manage ambiguous data science problems, and leveraging new technology to produce quantum leaps forward in understanding, such as via LLM-driven tooling.