Muhammad Hassaan Sohail is a Data Scientist and AI practitioner whose work sits at the intersection of rigorous technical engineering and meaningful community impact. He holds an M.S. in Applied Data Science (summa cum laude) from the University of Chicago and a B.Sc. in Finance and Marketing from the Lahore School of Economics, and brings deep expertise across the full data stack; from large-scale pipeline engineering and real-time data quality systems to machine learning, generative AI, and large language models (LLMs).

At WE in the World, Hassaan leads data science and data engineering and technical work in support of public health surveillance on behalf of federal and state agencies including the CDC, NIH, HRSA, and IDPH. He has designed and deployed automated data quality monitoring systems that track pipeline integrity in near-real-time across multi-agency government health data feeds; identifying and resolving anomalies before they reach downstream stakeholders.

His technical expertise spans the cutting edge of applied AI. He developed PRISM; an AI-powered multi-modal analytics platform recognized as Best in Show at the University of Chicago’s capstone program; integrating GPT-4o, OpenCV, and PyTorch. He has engineered RAG pipelines using LangChain, Pinecone, and OpenAI Embeddings, and fine-tuned large language models (LLaMA-7B) via Hugging Face PEFT, achieving a 31% improvement in BLEU-4 scores. His data engineering work includes automated ETL pipelines reducing manual preparation time by 60% and predictive models improving accuracy by 34%.