• Leading and driving planning, execution, and delivery of GenAI projects to achieve strategic goals and milestones.

• Collaborating closely with GenAI research, engineering, and product teams to align project objectives with broader organizational goals.

• Guiding the work of onshore and offshore vendors to complete data annotation projects.

● Overseeing 5+ simultaneous GenAI Safety data annotation/labeling projects handled by 6+ vendors, to collect and deliver high quality data sets for English, multilingual (20+ languages), and multimodal (text, speech, image) projects.

● Developed and executed a comprehensive weekly golden set testing framework, yielding a 5% improvement in vendor data quality within a 3-month period.

● Successfully onboarding and managing 6+ vendors, ensuring compliance with program requirements. Fostering strong vendor relationships by resolving data delivery blockers, coordinating support, leading strategic meetings, and tracking deliverables to meet deadlines.

● Leading a high-performing team of 10 Data Quality Analysts in the Safety domain, overseeing onboarding, training, and development to ensure seamless integration and optimal performance.

● Serving as a Subject Matter Expert on GenAI LLM Trust & Safety guidelines and annotation workflows, providing expert guidance and support to internal teams and vendor partners across English, multilingual, and multimodal workflows.

● Serving as a key liaison between the Safety Content Policy team and external vendors, facilitating timely communication and issue resolution, informing policy decisions, and ensuring vendor compliance with policy updates.

• Led data quality audits of white glove and in house PDO vendors for GenAI projects with 90+% accuracy , ensuring accurate labeling and analysis of large datasets for informed product decisions.

• Expert in AI Safety guidelines and labeling workflows, supporting project managers and product teams in implementing changes for improved workflows and product features.

● Composed, annotated, and validated Gen AI LLM Safety projects and Large Language Models training data.

Customer Behavior Analytics Finance

• Created and maintained an internal online knowledge repository for all Finance stakeholders across Amazon, consisting of complex information about Amazon’s free cashflow models, metrics, tools and how to correctly use them.

• The resource was approved to be used as onboarding material for new joiners to Worldwide Amazon Stores Finance organization and rated 4.9 out of 5 by users.

• Conducted customer discussions and surveys to best understand customer needs. Organized introductory events to demonstrate the resource.

• Supported ad hoc requests from finance and product stakeholders.

Oppia is an online learning platform focused on providing quality education to students who lack access to it.

➢ Analyzed Google Analytics data to understand trends in user behavior and product usage to influence strategy.

➢ Identified opportunities to drive growth, analyzed the performance of current referral websites and landing pages. Created a database for potential referral websites for Oppia.

➢ Monitored and reported on the Google Ads spend.