Wasiq Banday

Led the review and refinement of complex video annotations for SORA, OpenAI's video generation project, ensuring data integrity and alignment with model learning objectives. Identified patterns and improvement areas in annotation data to support fine-tuning Retrieval-Augmented Generation (RAG) pipelines, optimizing the relevance and accuracy of AI-generated outputs.

Produced detailed and context-aware video annotations supporting the training of SORA, OpenAI's pioneering video AI model across varied scenarios. Utilized Reinforcement Learning from Human Feedback (RLHF) and Supervised Fine-Tuning (SFT) techniques to generate high-quality training data and enhance AI model learning.

Analyzed service performance data to implement process improvements that enhanced client satisfaction and operational efficiency. Directed team training and development initiatives informed by data insights, achieving a 20% improvement in customer retention metrics.

Led data-driven educational initiatives in line with Sustainable Development Goal 4 (Quality Education). Conducted community research to design impactful programs, improving educational outcomes in underprivileged regions.

Pursued a dual degree program focusing on Business Administration and a Master of Business Administration with specializations in Marketing and Information Technology. Gained comprehensive knowledge in business principles, marketing strategies, and IT applications relevant to modern business environments.