Lead Data Scientist, Research, Multimodal Search

Minimum qualifications:

• Master's degree in Statistics, Data Science, Mathematics, Physics, Economics, Operations Research, Engineering, or a related quantitative field.
  
• 8 years of work experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or 6 years of work experience with a PhD degree.
  
• 2 years of experience as a people manager within a technical leadership role.

Preferred qualifications:

• 10 years of work experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or 8 years of work experience with a PhD degree.
  
• Experience in assessing opportunities and measuring performance of new products with few precedents or comparables.
• Understanding when to apply the cannon of existing tools and analysis, and when to forge something new.
• Ability to be comfortable doing unprecedented things, and thinking about things in new ways.

About the job

The mission of the Contextual Search team is to make Google Search even more useful by seamlessly answering questions motivated by your information context. This includes searching for things you see on your screen, as well as asking questions that reference the page you are on, the PDF you are reading, or the video you are watching.
By leveraging the computer vision capabilities developed through Google Lens, and the ability of LLMs to take in and synthesize multiple pieces of information context, we can answer new types of questions and make it easier for users to reach their information goals.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.
The US base salary range for this full-time position is $197,000-$291,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.
Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google.
By leveraging the computer vision capabilities developed through Google Lens, and the ability of LLMs to take in and synthesize multiple pieces of information context, we can answer new types of questions and make it easier for users to reach their information goals.
The US base salary range for this full-time position is $197,000-$291,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google.

Responsibilities

• Set and deliver the research agenda to understand users Search needs beyond text inputs. Identify data-backed solutions to meet needs by collaborating with Engineering, Program Managers, and User Research teams to land data-driven growth strategies.
• Use custom data infrastructure or existing data models as appropriate, using specialized knowledge. Design and evaluate models to mathematically express and solve defined problems with limited precedent.
• Design and instrument new metrics as needed. Set technical standards for evaluation and launch decisions.
• Own the process of gathering, extracting, and compiling data across sources via relevant tools (e.g., SQL, R, Python). Build processes to keep data front-of-mind for decision makers, and unblock launch decisions.
• Lead a team of analysts in framing problems, developing metrics, extracting, manipulating, and visualizing data. Implementing models, and influencing stakeholders through presentations and written communication.