Data Scientist, Search, Multimodal

Minimum qualifications:

• Bachelor's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field.
  
• 5 years of work experience with analysis applications (extracting insights, performing statistical analysis, or solving business problems), and coding (Python, R, SQL) or 2 years of experience with a Master's degree.

Preferred qualifications:

• Master's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field.
  
• 5 years of work experience with analysis applications (extracting insights, performing statistical analysis, or solving business problems), and coding (Python, R, SQL).

About the job

The Search Multimodal Data Science team is at the forefront of shaping the future of search. Our mission is to deeply understand and enhance user experiences by leveraging data from inputs including images (Lens), voice, and contextual signals. We drive product strategy and innovation for some of Google's fastest-growing Search surfaces, ensuring our AI-first features are intuitive, effective, and power new ways for users to find information and complete tasks, any way, anywhere.

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.

Responsibilities

• Drive growth analysis and user understanding, delving deep into user behavior patterns, identifying opportunities for growth, and understanding the end-to-end user journey across our multimodal surfaces.
• Conduct rigorous analysis for important launches, designing, implementing, and analyzing A/B tests and other experiments to measure the impact of new features and product changes, ensuring we make data-driven decisions.
• Contribute to our analysis infrastructure and AI upskilling efforts, helping to build and refine the tools, pipelines, and best practices our team uses, while also staying at the forefront of AI techniques to enhance our problem-solving capabilities and unlock new insights.