Nurse workforce optimization and scheduling in hospital units is a complex data science and operation research problem. Traditional manual estimation and preparation of nurse staffing and scheduling with the help of a subject matter expert might leads to over staffing or under staffing of different type of nurses such as core, float pool, overtime and agency, which impacts the patient care delivery and cost significantly. The situation becomes worse in case of emergency department as the patient head on bed occupancy is very dynamic in nature and many times the department might be overcrowded with no beds for the patients. Therefore, it is very difficult to design manual optimal workforce optimization of nurses for emergency units. To address this problem, we have developed methodologies to model emergency department head on bed occupancy and optimize various type of nurse staffing to run the hospital with optimal budget.