Senior Data Scientist, Contextual Search & AI

Socket.dev; Mountain View (CA); On-site; USD 163,000 - 236,000; Full time

Job summary

Google is seeking a Senior Data Scientist for its Contextual Search Data Science team in Mountain View. The role focuses on leveraging contextual data to shape search experiences, drive product strategy, and power AI-first features for billions of users worldwide.

The position emphasizes designing experiments, building analytics tools and pipelines, and mentoring junior data scientists as part of cross-functional collaboration with Engineering and Product teams.

Qualifications

• Bachelor's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field.
• 8 years of work experience using analytics to solve product or business problems, performing statistical analysis, and coding (e.g., Python, R, SQL) or 5 years of work experience with a Master's degree.

Responsibilities

• Delve deep into user behavior patterns, identifying opportunities for growth and understanding the end-to-end user journey across contextual search surfaces.
• Design, implement, and analyze A/B tests and other experiments to measure the impact of new contextual features and product changes.
• Build and refine the tools, pipelines, and best practices our team uses, while staying at the forefront of AI techniques to enhance our analytical capabilities.
• Guide complex, ambiguous projects from inception to completion, influence cross-functional roadmaps, and mentor junior data scientists on the team.

Skills

Analytics

Statistical analysis

Education

Bachelor's degree (quantitative field)

Master's degree

Tools

Python

R

SQL

Job description

Google is seeking a Senior Data Scientist for its Contextual Search Data Science team in Mountain View. The role focuses on leveraging contextual data to shape search experiences, drive product strategy, and power AI-first features for billions of users worldwide.

The position emphasizes designing experiments, building analytics tools and pipelines, and mentoring junior data scientists as part of cross-functional collaboration with Engineering and Product teams.