Principal Data Scientist - Safety

San Mateo, CA · San Mateo · USD 274,000-373,680 / year · 7+ years experience · Full-time · Onsite · Posted Oct 6, 2026

At a glance

The Principal Data Scientist for Safety will apply expertise in data science, statistics, and causal inference to improve the detection and mitigation of harmful user-generated content and violative behaviors.
This role involves establishing ground truth datasets, developing prevalence measurement methodologies, and collaborating with cross-functional teams to guide defensive strategies against safety threats.

Establish and monitor robust prevalence measurement methodologies to quantify harmful content and behavior.
Develop and validate comprehensive ground truth datasets for harmful UGC and violative behaviors.
Conduct exploratory analysis on current and emerging threat landscapes to provide strategic investment recommendations.
Design, implement, and analyze experiments for new moderation and safety enforcement features.
Leverage causal inference methodologies to measure the effectiveness of safety initiatives.
Communicate strategic insights and recommendations to leadership and cross-functional partners.
Partner with ML and Data Engineering teams to ensure detection systems are built on sound measurement frameworks.

10+ years of industry experience in data science, economics, analytics, or machine learning engineering.
7+ years of experience using scripting languages (Python, R) and big data tools (SQL, Hive, Spark, Airflow).
Knowledge of ML and Deep Learning via formal training or industry experience.
Ability to apply creative first-principles reasoning to solve ambiguous problems.
Experience developing large-scale safety or moderation systems.
Experience with content platforms, specifically user-generated content.
Advanced Degree and/or PhD in Statistics, Computer Science, Physics, Applied Math, Economics, or related quantitative fields.