Lead Data Scientist, Transparency & Observability - Trust and Safety

What you'll do

• Design observability systems spanning enforcement metrics, pipelines, monitoring, and reporting.
• Build governed, audit-ready data foundations and reliable data products, including systems for agent consumption.
• Lead AI-readiness strategy and cross-team adoption, from identifying opportunities to production deployment; mentor technical teams.

What they ask for

• 5+ years in Data Science, Data Engineering, Data Architecture, Analytics, or a related quantitative field, including technical leadership of cross-team initiatives.
• Track record designing scalable data ecosystems, including data modeling, governed analytics layers, and production pipelines on large-scale platforms.
• Strong SQL and Python skills; experience building data quality, monitoring, or observability solutions and organization-wide metrics frameworks.
• Understanding of AI architecture patterns and responsible AI practices applied to operational workflows; bachelor's degree or above in a quantitative discipline.

Nice to have

• Experience in Trust & Safety, regulatory reporting, or compliance; familiarity with transparency and regulatory requirements such as the EU Digital Services Act (DSA).
• Experience driving program and change management across global, cross-functional teams.

Tools

Hive, Spark, SQL, Python, RAG, embeddings

AI focus

Leads Trust & Safety AI readiness and architecture; applies AI patterns and responsible AI practices to operational workflows, builds data systems for agent consumption, and takes AI and data solutions from experimentation to reliable production.