Data Scientist, Research, Search Quality Trust (English, Portuguese)

Minimum qualifications:

• Master's degree in Statistics, Data Science, Mathematics, Physics, Economics, Operations Research, Engineering, a related quantitative field, or equivalent practical 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 experience analyzing data and creating reports with strong statistical, quantitative modeling, and forecasting skills.
• 3 years of experience in an applied research setting.
• Experience in survey research, excellent working knowledge of statistics, and proficiency in one or more statistical software packages (e.g., R, SPSS, Stata, SAS).
• Experience with Python, R, or other scripting languages.

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.

Core Ranking Data Science (DS) is part of the Quality AI and Lens DS team, whose mission is to drive product excellence and user and ecosystem growth for Search with data insights. Our team develops and supports evaluation methodology and metrics used to guide and develop Search Quality models and iteration, as well as the Search product as a whole. We work with Engineers, Researchers, and Product Managers within and outside of Search to bring helpful and trustworthy content to Search users.

Among other things, we work on Human and AI Rater quality and methodology, including LLM based Raters and hybrid metrics and methodology. We are working to push the boundaries of this emerging field. We also work on web ecosystem metrics and insights, enabling Search to better understand and nurture the web-content ecosystem, Search Quality experimentation, insights, and methodology, and Search Quality Trust — ensuring safe, reliable, and trustworthy information for Google Search users.

Google Research addresses challenges that define the technology of today and tomorrow. From conducting fundamental research to influencing product development, our research teams have the opportunity to impact technology used by billions of people every day.

Our teams aspire to make discoveries that impact everyone, and core to our approach is sharing our research and tools to fuel progress in the field -- we publish regularly in academic journals, release projects as open source, and apply research to Google products.

• Work with the DS team and Search Quality Engineering and Product teams to enable insights and data-driven decision making for Search Quality.
• Work with data sets and solve non-routine analytical challenges, applying analytical methods as required. Conduct end-to-end analysis including: data gathering and requirements specification, processing, analysis, ongoing deliverables, and presentations.
• Build and prototype analysis pipelines iteratively to provide insights at scale. Develop an understanding of data structures and goals, advocating for changes where needed for product development.
• Interact cross-functionally with a wide variety of teams, and work closely with Engineers to deeply understand product value and pain points for users, and identify opportunities for improving the Search product.
• Research and develop analysis, forecasting, and optimization methods to improve the quality of Google's user facing products.