Principal Data Scientist, Analytics & AI Platforms

C0035 LiveRamp, Inc.; San Francisco (CA); Hybrid; USD 194,000 - 228,000; Full time

Benefits offered by this job

Flexible PTO

Paid holidays

Work from home options

Paid parental leave

401K matching

Job summary

LiveRamp, Inc. seeks a Principal Data Scientist, Analytics to develop scalable data and analytics solutions and user-friendly tools for business teams.

You will shape data models, build pipelines, and deliver dashboards and predictive analytics across Product and Engineering, partnering with architects and data engineers to embed analytics in the product lifecycle. The role emphasizes experimentation strategy, model validation, and governance to ensure trustworthy insights and broad adoption

Qualifications

• MS or PhD in Computer Science, Statistics, Mathematics, or a related field.
• 10+ years of experience in Data Science and Analytics with high-impact product insights.
• Expert-level proficiency in Python and SQL; cloud experience (BigQuery) and hands-on DS modeling; familiarity with LLMs.

Responsibilities

• Self‑Service Analytics & Insights: design, build, certify reusable metrics, dashboards, and analytics products for Product and Engineering teams.
• Data Science, Modeling & Experimentation: develop predictive/causal models, conduct A/B tests, support roadmap with data-driven insights.
• Leadership: mentor analysts and data scientists; lead cross‑functional analytics projects and evangelize best practices.

Skills

Python

SQL

BigQuery

DS models

LLM/AI

Experimentation

Stakeholder communication

Education

MS/PhD in CS/Statistics/Math

Tools

dbt

Tableau

Job description

LiveRamp, Inc. seeks a Principal Data Scientist, Analytics to develop scalable data and analytics solutions and user-friendly tools for business teams.

You will shape data models, build pipelines, and deliver dashboards and predictive analytics across Product and Engineering, partnering with architects and data engineers to embed analytics in the product lifecycle. The role emphasizes experimentation strategy, model validation, and governance to ensure trustworthy insights and broad adoption