Opinion: STAT+: How to close biopharma’s data science and engineering skills gap
In biopharma research and development, laboratory data now exist in petabytes. Today’s fastest liquid-handling robots can dispense samples into 384 wells in a matter of seconds. Vaccines, which have traditionally been grown in eggs or cell cultures can now be printed. Algorithms are the path to discovering new materials. The pace of the industry’s technical innovation in the past five years alone has been head-spinning.
As the tools and techniques change, so do the demands on teams. Now common on biotech job boards are positions like cloud engineer, data scientist, automation engineer, software engineer, machine learning engineer, and computational biologist.
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