Staff Product Data Scientist: AI-Driven Analytics Lead

Google; Mountain View (CA); On-site; USD 192,000 - 279,000; Full time

Job summary

Google Mountain View is seeking a Staff Product Data Scientist to lead the evolution of data systems across merchant and communication products. You will bridge data science and software engineering, moving away from manual SQL pulls to self-healing data pipelines and AI-friendly semantic layers.

You will shape analyses, build autonomous agents, and drive measurable ROI by translating interaction data into actionable product recommendations for Google’s merchant ecosystem.

Qualifications

• Bachelor's degree in a quantitative field.
• 10 years of analytics experience with product/business problems, or 8 years with a Master's.
• Experience with ML/AI, coding, system design, or software development.

Responsibilities

• Develop AI agents capable of executing end-to-end data analysis, from exploring interaction data in Business Profiles and writing queries, to diagnosing metric shifts and generating product recommendations.
• Write and deploy production code to build data pipelines for Business Messaging and Business Agents.
• Structure our data warehouses so they are universally readable by internal AI systems and product surfaces, ensuring accurate, reliable, and reproducible query retrieval.
• Architect the statistical frameworks and infrastructure for A/B testing. Build automated systems that interpret experimental results, flag statistical noise, and output clear ship/no-ship recommendations.
• Serve as a technical benchmark for the data organization. Write clean, maintainable code (Python, SQL), and mentor executive team members on system architecture and advanced statistical methods.

Skills

Statistics

Analytics

Python

SQL

Machine learning

Education

Bachelor's degree

Master's degree

Tools

Python

R

SQL

Job description

Google Mountain View is seeking a Staff Product Data Scientist to lead the evolution of data systems across merchant and communication products. You will bridge data science and software engineering, moving away from manual SQL pulls to self-healing data pipelines and AI-friendly semantic layers.

You will shape analyses, build autonomous agents, and drive measurable ROI by translating interaction data into actionable product recommendations for Google’s merchant ecosystem.