Drive complex risk governance projects independently, define the safety operations roadmap, set success metrics (e.g., risk recall, precision, false positive rate), and partner across the organization to develop and execute action plans;
Focus on designing, implementing, and optimizing risk governance strategies specifically for the recommendation phase (e.g., feed distribution). Balance safety interventions with creator experience to minimize false positives and unwarranted visibility restrictions;
Leverage data analysis methodologies to monitor operational health, identify emerging risks in the recommendation ecosystem, and conduct deep dives into creator appeal cases (false positives) to iterate on distribution rules and policies
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Lead data annotation projects: manage the end-to-end execution of multiple projects, ensuring performance targets and SLAs are met.
Serve as the primary stakeholder interface for key internal requestors: translate product or business needs into clear labeling project requirements, align on targets, support workforce management planning, and develop delivery plans.
Drive delivery governance and cross-functional collaboration: establish operating rhythms, execution reviews, and escalation frameworks across QA, vendor, and business teams.
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Lead data annotation projects: manage the end-to-end execution of multiple projects, ensuring performance targets and SLAs are met.
Serve as the primary stakeholder interface for key internal requestors: translate product or business needs into clear labeling project requirements, align on targets, support workforce management planning, and develop delivery plans.
Drive delivery governance and cross-functional collaboration: establish operating rhythms, execution reviews, and escalation frameworks across QA, vendor, and business teams.
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