Allyson Strable

Trust & Safety-focused behavioral analyst with advanced training in multivariate regression, causal inference, and risk modeling applied to large-scale human behavior data. Experienced in developing analytical frameworks to detect emerging risk signals, evaluate policy enforcement effectiveness, and measure intervention impact. Skilled in statistical diagnostics, metrics development, and translating complex findings into scalable, data-driven recommendations for cross-functional teams across policy, product, and operations. Committed to evidence-based harm prevention and responsible data governance in high-growth platform environments.

• Designed a multivariate regression modeling framework evaluating relationships among 3+ behavioral predictors and system-level outcomes, incorporating interaction effects to assess context-dependent risk amplification
• Conducted full diagnostic validation (multicollinearity via VIF, residual analysis, heteroskedasticity testing) and proposed model comparison strategy to ensure statistical robustness and signal reliability
• Operationalized 5+ abstract psychological constructs into measurable indicators to support metrics development and outcome evaluation
• Synthesized peer-reviewed research sources to inform evidence-based model specification and intervention impact strategy
• Translated quantitative modeling outputs into executive-ready summaries and stakeholder-facing recommendations to guide data-driven decision-making
• Applied human-subject research ethics and bias-aware evaluation frameworks to promote responsible and defensible behavioral data interpretation