Senior Data Scientist, Ads Integrity

Responsibilities

• Lead the measurement and detection strategy for ads fraud by defining fraud taxonomies, labels, sampling plans, metrics, and evaluation frameworks that make performance measurable and defensible.
• Analyze large, complex datasets and networks of behavior to uncover emerging fraud patterns, size their impact, identify root causes, and translate findings into detection and enforcement requirements.
• Design and develop scalable ads fraud detection and enforcement pipelines in partnership with Engineering and Machine Learning, including feature generation, rules and models, near-real-time scoring, actioning, review feedback loops, and observability.
• Own the full detection lifecycle: backtesting, threshold calibration, offline and online evaluation, launch validation, experimentation, monitoring, drift detection, incident response, rollback, and retirement.
• Build and maintain statistical, machine learning, and GenAI-enabled models or prototypes that improve fraud detection, risk identification, investigator efficiency, and enforcement quality.
• Balance fraud loss, platform and advertiser risk, customer experience, false-positive costs, operational capacity, and business goals when recommending detection thresholds and enforcement strategies.
• Partner across Ads and Safety to shape strategy and roadmaps, strengthen data foundations, close policy and enforcement gaps, and ensure solutions meet governance and compliance standards.
• Translate complex analyses into clear narratives and actionable recommendations for technical and non-technical stakeholders, including senior leaders, and mentor other data scientists and analysts.

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