Data Scientist II, Research, Lens and Contextual Search

1 Month ago • 2 Years + • Data Analyst • $108,000 PA - $158,000 PA

Job Summary

Job Description

This Data Scientist II role at Google Search focuses on improving the search experience. You'll work closely with engineering teams, evaluating framework changes and understanding experiment interactions. Responsibilities include identifying and clarifying business questions, developing roadmaps to accelerate feature discovery, and gathering data from various sources. You'll need to translate business questions into tractable analysis, build mathematical models, and communicate findings effectively. The role requires strong analytical skills, proficiency in statistical modeling and programming (Python, R, SQL), and experience with large datasets. You'll be a key contributor to enhancing Google Search's capabilities and impact on billions of users globally.
Must have:
  • Master's degree in quantitative field
  • Experience in statistical modeling/ML
  • Data analysis & manipulation skills (SQL, Python, R)
  • Collaboration and communication skills
  • Understanding user interaction with search
Good to have:
  • 2+ years experience solving product problems
  • Experience with log-based pipelines
  • Understanding of experiment design
  • Excellent attention to detail and accuracy
Perks:
  • Bonus
  • Equity
  • Benefits

Job Details


Minimum qualifications:

  • Master's degree in Statistics, Mathematics, Physics, Economics, Operations Research, Engineering, a related quantitative field, or equivalent practical experience.
  • Experience in one or more areas of statistical or ML modeling, experimentation or survey design, building and reading from logs-based pipelines.

Preferred qualifications:

  • 2 years of work experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis.
  • Understanding of how users want to interact with Search.
  • Excellent attention to investigative accuracy and scale (e.g., peer reviews, version-controled analysis artifacts).

About the job

In this role, you will be embedded with engineering teams to understand and evaluate framework changes. You will understand how experiments interact with projects outside the immediate team. You will advocate for users, know when complex analytics are warranted versus when summary statistics can solve a problem, collaborate closely with technical experts, and confidently communicate what metrics mean.

In Google Search, we're reimagining what it means to search for information – any way and anywhere. To do that, we need to solve complex engineering challenges and expand our infrastructure, while maintaining a universally accessible and useful experience that people around the world rely on. In joining the Search team, you'll have an opportunity to make an impact on billions of people globally.

The US base salary range for this full-time position is $108,000-$158,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. The range displayed on each job posting reflects the minimum and maximum target salaries for the position across all US locations. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.

Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about .

Responsibilities

  • Collaborate with stakeholders in cross-projects and team settings to identify and clarify business or product questions to answer. Provide feedback to translate and refine business questions into tractable analysis, evaluation metrics, or mathematical models.
  • Develop roadmaps to accelerate feature discovery, analyzing clusters of use patterns to gauge satisfaction and opportunities to improve experiences, and scoping new opportunities where searching with context can help accelerate or create new Search needs.
  • Gather information, business goals, priorities, and organizational context around the questions to answer, as well as the existing and upcoming data infrastructure.
  • Own the process of gathering, extracting, and compiling data across sources via relevant tools (e.g., SQL, R, Python). Format, re-structure, or validate data to ensure quality, and review the dataset to ensure it is ready for analysis.

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