High profile use cases of modeling and forecasting dynamic phenomena include:
The role of data scientist is a relatively new addition to the research and development (R&D) landscape within large life science — pharmaceutical, medical nutrition, biotechnological — companies. For early career data scientists, or established data scientists interested in a move into life sciences research, there are increasing opportunities in this field as it matures and gains recognition alongside established scientific disciplines.
To be a successful data scientist in a life sciences research environment, particularly in a larger company, requires many of the same skills and experiences as in any other industry. But there are some notable differences: