Define and track core metrics for spam prevalence, false positives, enforcement efficacy, and user impact. Develop automated dashboards, anomaly detection alerts, and reporting pipelines to monitor ecosystem health in real time. Design and execute A/B tests and counterfactual analyses to evaluate the efficacy and side effects of anti-spam rules, ML model updates, and UI interventions. Partner closely with Product, Engineering, Policy, and UX teams to identify spam trends, prioritize enforcement roadmaps, and balance security with user engagement.
Conduct exploratory data analyses on evolving adversarial behaviors in conversational messaging and present technical insights to cross-functional stakeholders. Evaluate and iterate on statistical models, heuristics, and classification algorithms (e.g., text classifiers, graph signals, behavioral anomaly detection) to detect spam, phishing, and unwanted traffic across P2P RCS and commercial RBM channels.
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