Lead Data Scientist — AI Transparency & Observability

TikTok; New York (NY); On-site; USD 219,000 - 354,000; Full time

Job summary

TikTok in New York is seeking a Lead Data Scientist for Transparency & Observability within Trust & Safety. You will design data foundations, metrics, and AI readiness to explain and improve enforcement systems.

You will lead architecture, governance, and end-to-end data pipelines, collaborating with product, engineering, policy, and legal teams to land scalable, auditable solutions and a unified view of enforcement outcomes.

Qualifications

• 5+ years in data science, data engineering, or related fields with cross-team leadership.
• Proven track record designing scalable data ecosystems and production pipelines.
• Strong SQL and Python skills.
• Experience building data quality, monitoring, or observability solutions.
• Solid understanding of AI patterns and responsible AI practices.
• Ability to translate business problems into technical strategy and influence stakeholders.
• Bachelor's degree or higher in a quantitative field.

Responsibilities

• Architect Transparency & Observability systems for Trust & Safety.
• Design end-to-end observability for the enforcement lifecycle.
• Set standards for metrics, anomaly detection, and alerting.
• Build governed, AI-ready data foundations with quality and lineage.
• Design ETL pipelines and workflow orchestration for reliable data products.
• Build data systems for agent consumption across Trust & Safety.
• Drive AI readiness and technical leadership across Trust & Safety.
• Own the long-term technical roadmap and drive cross-team adoption.
• Create reusable architecture principles and mentor teams.

Skills

SQL

Python

Data architecture

Leadership

Stakeholder influence

AI concepts

Education

Bachelor's or higher in a quantitative discipline

Tools

Hive

Spark

Airflow

Job description

TikTok in New York is seeking a Lead Data Scientist for Transparency & Observability within Trust & Safety. You will design data foundations, metrics, and AI readiness to explain and improve enforcement systems.

You will lead architecture, governance, and end-to-end data pipelines, collaborating with product, engineering, policy, and legal teams to land scalable, auditable solutions and a unified view of enforcement outcomes.