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Strong Tier-1 brand plus common mid-level data title increases applicant density despite niche Trust and Safety focus.
Specialized Trust and Safety analytics and moderation expertise limits cross-industry transferability.
Mandatory Master's degree, explicit four-year requirement, and core SQL/Python skills enforce strict shortlisting.
Own and advance statistical methodologies and sampling frameworks to monitor enforcement quality and machine learning precision across 200+ classifiers.
Lead quantitative analytics and data science strategy for automated content moderation, including launch readiness and impact assessments.
Design and execute large-scale statistical experiments and multivariate Root Cause Analysis to optimize human review processes and operational efficiency.
Master's degree in quantitative discipline or equivalent experience.
At least 4 years experience using analytics, coding (Python, R, SQL), and querying distributed databases.
At least 4 years experience using SQL for quantitative data management.
Work Experience Required: Minimum 4 years explicitly mentioned, preferred 7 years relevant experience in Trust and Safety or related data science roles.
Experienced in Trust and Safety, abuse detection, content moderation, or large-scale operations analytics with advanced statistical skills.
Skilled in designing and managing complex operational experiments and root cause analyses for high-stakes product environments.
Able to collaborate across engineering, product, and operations teams to deploy scalable metrics infrastructure and influence product strategy.