• Lead large-scale AI and research programs focused on data labeling, annotation, and evaluation for model development.

• Direct program execution for AI and research initiatives, translating organizational strategy into operational roadmaps, workflows, and measurable outcomes.

• Manage a globally distributed team of 100+ researchers and annotators, overseeing hiring, performance management, and delivery across multiple work streams.

• Led a team of 50+ data analysts and data annotators across 14+ AI data operations projects, ensuring consistent execution, high-quality labeling, and reliable delivery.

• Partnered with leadership and engineering teams to define and implement KPI frameworks for data quality, throughput, and operational performance.

• Built and supported three high-performing data operations teams, establishing workflows, auditing standards, and training programs to drive accuracy, consistency, and efficiency.

• Delivered training and eval datasets for LLM models, contributing to 87% hallucination reduction and measurable GenAI product gains.

• Authored and maintained campaign documentation and quality guidelines, clarifying expectations and streamlining collaboration with engineering partners.

• Mentored peers and led informal knowledge shares to build team capability and foster cross-pollination of technical insights, achieving 20%+ improvements in throughput and quality.