Senior Product Data Scientist, AI & Analytics

Google; Boulder (CO); On-site; USD 192,000 - 278,000; Full time

Benefits offered by this job

Health, dental, vision, life insurance

401(k) with company match

Paid time off 20 days/year

Sick time 40 hours/year (Seattle 69)

Maternity Leave 28-30 weeks

Baby Bonding Leave 18 weeks

13 paid holidays

Job summary

Google is hiring a Data Scientist/Analytics Engineer to support Workspace products used by billions of users. You will act as an analytics expert, turning data into actionable guidance for engineering and product teams while crafting narratives from quantitative insights.

You will collaborate across product and engineering to build scalable data models and self-serve analytics tooling, shaping decision-making with data-driven recommendations and dashboards.

Qualifications

• Bachelor's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or related quantitative field.
• 10 years of analytics experience or 8 years with a Master's.
• 8 years experience in product analytics concepts (engagement metrics, funnel analysis, A/B testing).
• 8 years data modeling and semantic layer design responsibilities.
• Experience operating distributed data processing engines.

Responsibilities

• Lead research and development of metric frameworks to evaluate effectiveness and adoption of Generative AI within Workspace products.
• Partner with product engineering and data teams to clarify ambiguity, define roles, and manage telemetry projects from inception to execution.
• Design and build scalable data models and analytical architecture connecting data across product domains.
• Scope and manage self-serve analytics initiatives by creating unified semantic layers and dashboards.

Skills

Analytics

Statistics

SQL

Python

A/B testing

Education

Bachelor's degree in quantitative field

Tools

Python

SQL

R

Job description

Google is hiring a Data Scientist/Analytics Engineer to support Workspace products used by billions of users. You will act as an analytics expert, turning data into actionable guidance for engineering and product teams while crafting narratives from quantitative insights.

You will collaborate across product and engineering to build scalable data models and self-serve analytics tooling, shaping decision-making with data-driven recommendations and dashboards.