Google

Senior Data Scientist, Real World Journeys, Research, Search

Google Mountain View, California, United States · $174K–$252K/yr

Software Development · 10,001+ employees

5 h ago
data-scientist Senior (5-10 yrs) Full-time United States
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About the role

The role involves partnering with product and engineering teams to drive advanced analytics, metric research, and user journey insights for Google Search verticals. You will lead human evaluations, design experiments, and apply advanced modeling techniques like LLMs to improve search product performance.

What they look for

Python R SQL Data Science Statistics Machine Learning LLM Gemini Models Experiment Design A/B Testing Metric Development User Journey Analysis Product Analytics Search Engineering Communication Skills Problem-solving

Requirements

Candidates must hold a Master's degree or PhD in a quantitative field such as Statistics, Data Science, or Engineering. A minimum of 5 years of experience in analytics, coding, and database querying is required, with preference given to those with 8 years of relevant experience.

Benefits

Bonus Equity Health Insurance

Full description

Minimum qualifications:

  • Master's degree in Statistics, Data Science, Mathematics, Physics, Economics, Operations Research, Engineering, or a related quantitative field.
  • 5 years of experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or 3 years of experience with a PhD degree.

Preferred qualifications:

  • 8 years of experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or 6 years of experience with a PhD degree.
  • Excellent problem-framing, problem-solving and team collaboration skills.
  • Excellent communication skills, especially in communicating technical and statistical concepts clearly and concisely among audiences across different levels.
  • Excellent coding skills with the ability to understand and update production codes.

About the job:

As a part of Real World Journeys Experiences Data Science Team, you will support metrics research, and drive advanced analytics and user journey insights for numerous commercial search verticals, such as Google Flights, Hotels, Things to do, Food, Services, Auto, Finance etc.

In this role, you will work cross-functionally with multiple technical leads from Search Engineering and Product to advanced metric capabilities. You will need to apply advanced modeling techniques (LLM, Gemini models) for ML based metrics, Human Evaluation methods and design research based on user-survey data. Your responsibilities include metric development, product performance investigation, experiment design, and user journey analysis.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.Individual pay is determined by factors including job-related skills, experience, and relevant education or training.

US: $174000 - $252000 (USD) + 15% bonus target + equity + benefits

Learn more about benefits at Google. Responsibilities:

  • Partner with Product and Engineering teams of Real World Journeys to provide investigative thought leadership, support metrics research and advanced statistical analysis of user journeys on search.
  • Collaborate cross-functionally with teams across Google Search, leading Search AI Mode experiences projects and future AI bets of Google Search, such as, Agentic Search.
  • Lead Human Evaluations and Auto-rater evaluations for Product launches.
  • Identify metric improvement areas, design new metrics and evaluation methods by working cross-functionally.
  • Support teams with advanced experimentation methods, detecting user learning effects and drive actionable user insights from deep A/B testing metrics analysis.

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