Staff Data Scientist, Discover Personalization and Quality

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

Staff Data Scientist for Google Discover Personalization and Quality team, focusing on improving retrieval and ranking ML systems to deliver personalized content. This role involves analyzing systems, leading research, collaborating with engineering and product teams, and leveraging AI/LLM tools to enhance user experience and product growth.

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.

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.
  • 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.