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Growth Data Science Analyst, Google Labs and Workspace

Google
San Francisco, USA
Senior · 6+ years experience
Onsite
USD 163000-236000 / year
Discovered 1 weeks ago
pythonsql

Full Job Posting

Responsibilities

  • Architect and maintain unified full-funnel growth data pipelines and executive dashboards tracking acquisition, activation, adherence across Labs and Workspace products.
  • Build and automate dynamic first-party audience cohorting tables to power real-time lifecycle and remarketing triggers in Google Notification Platform, Chime mobile push, and Audience Builder.
  • Audit and validate end-to-end event instrumentation and conversion tracking pipelines—identifying and fixing data discrepancies between product logs, GA4, and Google Ads conversion imports.
  • Design, size, and analyze rigorous A/B, multi-cell, and geo-experimentation studies to measure true incremental lift across paid media, customer relationship management (CRM) lifecycle, and site optimization initiatives.
  • Develop reusable AI/agentic analytics workflows, model context protocol (MCP) tools, and automated anomaly-detection scripts that enable the growth team to self-serve cohort sizing and campaign diagnostics at machine speed.

Minimum qualifications:

  • Master's degree in a quantitative discipline such as Statistics, Engineering, Sciences, or equivalent practical experience.
  • 4 years of experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis.
  • 4 years of experience building agentic analytics workflows, custom skills, or automated pipelines.
  • 4 years of experience in SQL and Python or R for data modeling, cohort analysis, randomized controlled trials (A/B testing), holdback experiments, causal inference/incrementality models, and workflow automation.
  • 4 years of experience in growth analytics, marketing data science, or product analytics.

Preferred qualifications:

  • 6 years of experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis.

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