Job Description
📋 Description Design and implement robust measurement frameworks to evaluate trust and safety initiatives and Lead design, execution, and analysis of experiments and quasi-experiments where A/B testing may not Develop statistical, Bayesian, and causal inference models to assess risk and estimate treatment Partner with product, engineering, operations, and policy teams to translate findings into Produce leadership-ready analyses, visualizations, and presentations for technical and Evaluate ML system performance with rigorous measurement methodologies and causal interpretations. 🎯 Requirements Master's degree in Statistics, Economics, CS, Mathematics, or quantitative field with 5+ years in Deep expertise in experimentation design, causal inference methodologies, and statistical analysis. Strong experience with Bayesian modeling for uncertainty quantification and decision support. Advanced SQL and Python or R for data analysis and modeling. Proven ability to lead complex analytical initiatives and influence cross-functional stakeholders. Strong ML evaluation understanding and translating insights into business strategy. 🎁 Benefits Competitive base salary from $179,000 to $210,000 USD, depending on experience and location. Eligibility for performance bonuses and equity awards. Employee travel credits. Comprehensive health and benefits package. Fully remote role within eligible U.S. states, with occasional team offsites or office High-visibility initiatives with significant business and customer impact.
