Remote job
Senior Data Scientist, Ads Integrity
Job details
About this role
Role overview
A senior data scientist position focused on protecting the integrity of the advertising experience on a large, consumer-facing platform. The role centers on using analytics, statistical modeling, and machine learning to detect, measure, and reduce ads-related harms such as fraud, policy violations, and low-quality creative. It is a remote, U.S.-based role that partners closely with engineering, policy, and trust & safety teams.
Responsibilities
- Design and develop machine learning models and statistical methods that detect policy-violating ads, fraudulent activity, and emerging integrity risks at scale - Define the metrics, monitoring, and evaluation frameworks that measure ads quality and the impact of integrity interventions - Lead end-to-end analytical projects, from problem framing and data exploration through experimentation, modeling, and post-launch review - Partner with engineering, product, policy, and operations counterparts to translate integrity goals into measurable signals and product actions - Communicate findings, tradeoffs, and recommendations clearly to both technical and non-technical audiences across the organization
Requirements
- Several years of senior-level experience as a data scientist or applied scientist, with demonstrated ownership of production-grade analyses or models - Strong foundation in statistics, machine learning, experimental design, and causal inference - Proficiency querying and working with large-scale behavioral, transactional, or text data - Experience collaborating cross-functionally with engineering, product, policy, or operations partners to influence product or policy decisions - Excellent written and verbal communication skills, including the ability to frame ambiguous problems and explain technical conclusions to diverse audiences
Nice to have
- Background in trust & safety, ads quality, content moderation, fraud detection, or a closely related integrity-focused domain - Familiarity with advertising systems, auction dynamics, or advertiser-facing products