Data science attracts a variety of different backgrounds. From my professional experience, I’ve worked with colleagues who were once:
- Nuclear Physicists
- Post-docs researching Gravitational Waves
- PhD’s in Computational Biology
- Linguists
just to name a few.
It is wonderful to be able to meet such a diverse set of backgrounds and I have seen such a variety of minds lead to the growth of a creative and effective Data Science function.
However, I have also seen one big downside to this variety:
Everyone has had different levels of exposure to key Software Engineering concepts, resulting in a patchwork of coding skills.
As a result, I have seen work done by some data scientists that is brilliant, but is:
- Unreadable — you have no idea what they are trying to do.