Data Science Research, Search AI (English, Portuguese)

1 Month ago • 3-5 Years • Data Analyst

Job Summary

Job Description

The Search AI Overview Data Science team at Google is seeking a Data Scientist to leverage data and advanced analytics to enhance the search experience, particularly within the context of GenAI. Responsibilities include collaborating with stakeholders to define analytical problems, designing and evaluating models, gathering and processing data from various sources (using SQL, R, and Python), and ensuring data quality. The role involves working across projects, translating business questions into tractable analyses, and contributing to the evolution of Google Search for billions of users. The ideal candidate will have strong analytical skills, programming proficiency (Python, R, SQL), and experience in statistical modeling and forecasting, along with fluency in English and Portuguese for client interaction.
Must have:
  • Master's degree in quantitative field or equivalent experience
  • 3+ years experience in data analytics and problem-solving
  • Proficiency in Python, R, SQL
  • Fluent in English and Portuguese
  • Experience with statistical modeling and forecasting
Good to have:
  • PhD degree
  • 5+ years of experience in data analytics
  • 4+ years experience analyzing data and creating reports
  • Experience in applied research
  • Experience with survey research

Job Details


Minimum qualifications:

  • Master's degree in Statistics, Data Science, Mathematics, Physics, Economics, Operations Research, Engineering, or a related quantitative field or related equivalent experience.
  • 3 years of work experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or a PhD degree.
  • Ability to communicate in English and Portuguese fluently to support client relationship management in this region.

Preferred qualifications:

  • 5 years of work experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or a PhD degree.
  • 4 years of work experience analyzing data and creating reports with statistical, quantitative modeling, and forecasting.
  • 3 years of experience in an applied research setting.
  • Experience with Python, R, or other scripting languages.
  • Experience in survey research.
  • Knowledge of statistics and a statistical software package (e.g., R, SPSS, Stata, SAS).

About the job

At Google, data drives all of our decision-making. Quantitative Analysts work all across the organization to help shape Google's business and technical strategies by processing, analyzing and interpreting huge data sets. Using analytical excellence and statistical methods, you mine through data to identify opportunities for Google and our clients to operate more efficiently, from enhancing advertising efficacy to network infrastructure optimization to studying user behavior. As an analyst, you do more than just crunch the numbers. You work with Engineers, Product Managers, Sales Associates and Marketing teams to adjust Google's practices according to your findings. Identifying the problem is only half the job; you also figure out the solution.

The mission of Search AI Overview Data Science team is to leverage data, measurement methodologies, analysis insights and modeling to help improve Search experience in the context of latest GenAI capabilities and unlock new ways/use cases on how billions of users interact with Google search.

In Google Search, we are re-imagining 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 will have an opportunity to make an impact on billions of people globally.

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.
  • Use custom data infrastructure or existing data models as appropriate, using specialized knowledge. Design and evaluate models to solve defined problems with limited precedent.
  • 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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