Senior Data Scientist, Research, Search
@ Google

Mountain View, CA
$200,000
On Site
Full Time
Posted 21 days ago

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Job Details

Overview

The Senior Data Scientist, Research, Search at Google will evaluate and improve Google products, collaborate with multidisciplinary teams, and bring scientific excellence to product creation, development, and improvement. This role specifically focuses on revolutionizing the Google Search experience with the latest GenAI model capabilities.

Minimum and Preferred Qualifications

Minimum qualifications: Master’s degree in a quantitative field (Statistics, Data Science, Mathematics, Physics, Economics, Operations Research, Engineering or related) with 5 years of relevant work experience using analytics, coding (Python, R, SQL), database querying, or statistical analysis. Alternatively, a PhD with 3 years experience.

Preferred qualifications: 8 years of work experience using these skills or a PhD with 6 years experience.

Responsibilities

  • Collaborate with stakeholders to clarify product and business queries.
  • Translate business questions into tractable analytics and models.
  • Design and evaluate models with custom or existing data infrastructures.
  • Gather, extract, and compile data using SQL, R, and Python.
  • Ensure data quality and readiness for analysis.

Location & Compensation

Candidates may choose their preferred working location from Mountain View, CA or New York, NY. The full-time US base salary range is $166,000-$244,000 plus bonus, equity, and benefits.

Key Skills/Competency

  • Data Science
  • Analytics
  • Statistical Analysis
  • Python
  • R
  • SQL
  • GenAI
  • Modeling
  • Collaboration
  • Problem Solving

How to Get Hired at Google

🎯 Tips for Getting Hired

  • Customize your resume: Highlight analytics and modeling projects.
  • Research Google culture: Understand their mission and innovation.
  • Prepare for technical interviews: Review Python, R, and SQL.
  • Showcase collaborative work: Demonstrate teamwork and impact.

📝 Interview Preparation Advice

Technical Preparation

Practice Python and R coding challenges.
Review SQL query optimization techniques.
Study advanced statistical modeling methods.
Analyze past GenAI project case studies.

Behavioral Questions

Describe teamwork on complex projects.
Explain problem-solving under pressure.
Discuss past cross-functional collaborations.
Share handling conflicting priorities.

Frequently Asked Questions